Corrigendum: Genetic overlap and causality between COVID-19 and multi-site chronic pain: the importance of immunity.

[This corrects the article DOI: 10.3389/fimmu.2024.1277720.].

The Next-Generation Probiotic E. coli 1917-pSK18a-MT Ameliorates Cadmium-Induced Liver Injury by Surface Display of Metallothionein and Modulation of Gut Microbiota.

Cadmium (Cd) is recognized as being linked to several liver diseases. Currently, due to the limited spectrum of drugs available for the treatment of Cd intoxication, developing and designing antidotes with superior detoxification capacity and revealing their underlying mechanisms remains a major challenge. Therefore, we developed the first next-generation probiotic E. coli 1917-pSK18a-MT that delivers metallothionein (MT) to overcome Cd-induced liver injury in C57BL/6 mice by utilizing bacterial surface display technology. The results demonstrate that E. coli 1917-pSK18a-MT could efficiently express MT without altering the growth and probiotic properties of the strain. Moreover, we found that E. coli 1917-pSK18a-MT ameliorated Cd contamination-induced hepatic steatosis, inflammatory cell infiltration, and liver fibrosis by decreasing the expression of aminotransferases along with inflammatory factors. Activation of the Nrf2-Keap1 signaling pathway also further illustrated the hepatoprotective effects of the engineered bacteria. Finally, we showed that E. coli 1917-pSK18a-MT improved the colonic barrier function impaired by Cd induction and ameliorated intestinal flora dysbiosis in Cd-poisoned mice by increasing the relative abundance of the Verrucomicrobiota. These data revealed that the combination of E. coli 1917 and MT both alleviated Cd-induced liver injury to a greater extent and restored the integrity of colonic epithelial tissues and bacterial dysbiosis.

Genetic overlap and causality between COVID-19 and multi-site chronic pain: the importance of immunity.

Background: The existence of chronic pain increases susceptibility to virus and is now widely acknowledged as a prominent feature recognized as a major manifestation of long-term coronavirus disease 2019 (COVID-19) infection. Given the ongoing COVID-19 pandemic, it is imperative to explore the genetic associations between chronic pain and predisposition to COVID-19. Methods: We conducted genetic analysis at the single nucleotide polymorphism (SNP), gene, and molecular levels using summary statistics of genome-wide association study (GWAS) and analyzed the drug targets by summary data-based Mendelian randomization analysis (SMR) to alleviate the multi-site chronic pain in COVID-19. Additionally, we performed a latent causal variable (LCV) method to investigate the causal relationship between chronic pain and susceptibility to COVID-19. Results: The cross-trait meta-analysis identified 19 significant SNPs shared between COVID-19 and chronic pain. Coloc analysis indicated that the posterior probability of association (PPH4) for three loci was above 70% in both critical COVID-19 and COVID-19, with the corresponding top three SNPs being rs13135092, rs7588831, and rs13135092. A total of 482 significant overlapped genes were detected from MAGMA and CPASSOC results. Additionally, the gene ANAPC4 was identified as a potential drug target for treating chronic pain (P=7.66E-05) in COVID-19 (P=8.23E-03). Tissue enrichment analysis highlighted that the amygdala (P=7.81E-04) and prefrontal cortex (P=8.19E-05) as pivotal in regulating chronic pain of critical COVID-19. KEGG pathway enrichment further revealed the enrichment of pleiotropic genes in both COVID-19 (P=3.20E-03,Padjust=4.77E-02,hsa05171) and neurotrophic pathways (P=9.03E-04,Padjust =2.55E-02,hsa04621). Finally, the latent causal variable (LCV) model was applied to find the genetic component of critical COVID-19 was causal for multi-site chronic pain (P=0.015), with a genetic causality proportion (GCP) of was 0.60. Conclusions: In this study, we identified several functional genes and underscored the pivotal role of the inflammatory system in the correlation between the paired traits. Notably, heat shock proteins emerged as potential objective biomarkers for chronic pain symptoms in individuals with COVID-19. Additionally, the ubiquitin system might play a role in mediating the impact of COVID-19 on chronic pain. These findings contribute to a more comprehensive understanding of the pleiotropy between COVID-19 and chronic pain, offering insights for therapeutic trials.

Investigating the shared genetic architecture between attention-deficit/hyperactivity disorder and risk taking behavior: A large-scale genomewide cross-trait analysis.

BACKGROUND: This study aims to explore the genetic architecture shared between Attention-Deficit/Hyperactivity Disorder (ADHD) and risk behavior. METHODS: Based on the latest large-scale Genome-wide association studies (GWAS), we firstly employed Linkage disequilibrium score regression (LDSC) and Local Analysis of Variant Association (LAVA) to investigate the genetic correlation between risk behavior and ADHD. Then, we conducted cross-trait analysis to identified the Pleiotropic loci. Finally, bidirectional Mendelian randomization analysis (MR) was applied to examine the causal relationship. RESULTS: We found a significant positive genetic correlation between ADHD and risk-taking behavior (rg = 0.351, p = 6.50E-37). The cross-trait meta-analysis identified 27 significant SNPs shared between ADHD and risk behavior. The most significant locus, located near the CADM2 gene on chromosome 3, had been identified associated with this two trait (pADHD = 3.07E-05 and prisk-taking behavior = 2.47E-30). The same situation can also be observed near the FOXP2 gene on chromosome 7 (rs8180817, pmeta = 5.72E-21). We found CCDC171 gene and other genes played a significant role in ADHD and risk behavior in mRNA level. Bidirectional MR analysis found a causal relationship between them. LIMITATION: The majority of our data sources were of European origin, which may limit the generalizability of our findings to other ethnic populations. CONCLUSION: This article reveals in depth the shared genetic structure between ADHD and risk-taking behavior, finding a significant positive genetic correlation between ADHD and risk-taking behavior. Providing insights for the future treatment and management of these two traits.

Investigating the shared genetic architecture between COVID-19 and obesity: a large-scale genome wide cross-trait analysis.

Observational studies have reported high comorbidity between obesity and severe COVID-19. The aim of this study is to explore whether genetic factors are involved in the co-occurrence of the two traits. Based on the available genome-wide association studies (GWAS) summary statistics, we explored the genetic correlation and performed cross-trait meta-analysis (CPASSOC) and colocalization analysis (COLOC) to detect pleiotropic single nucleotide polymorphisms (SNPs). At the genetic level, we obtained genes detected by Functional mapping and annotation (FUMA) and the Multi-marker Analysis of GenoMic Annotation (MAGMA). Potential functional genes were further investigated by summary-data-based Mendelian randomization (SMR). Finally, the casualty was identiied using the latent causal variable model (LCV). A significant positive genetic correlation was revealed between obesity and COVID-19. We found 331 shared genetic SNPs by CPASSOC and 13 shared risk loci by COLOC. At the genetic level, We obtained 3546 pleiotropic genes, among which 107 genes were found to be significantly expressed by SMR. Lastly, we observed these genes were mainly enriched in immune pathways and signaling transduction. These indings could provide new insights into the etiology of comorbidity and have implications for future therapeutic trial.

Investigation of low-temperature partitioning with dispersive solid-phase extraction for quantification of pesticides in apples followed by electrospray-ionization mobility spectrometry: Comparison with conventional procedure.

Ion mobility spectrometry (IMS) has a promising application prospect in food surveillance. However, due to the complexity of food matrix and trace levels of pesticide residues, the effective and rapid detection of pesticides by IMS has been a challenge, especially when using electrospray ionization (ESI) as an ion source. In this study, low-temperature partitioning with dispersive solid-phase extraction (LTP-dSPE) was explored and compared with conventional procedures. Both methods were validated for the quantification of eight pesticides in apples, obtaining a limit of detection (LOD) of 0.02-0.12 mg/kg for LTP-dSPE and 0.02-0.09 mg/kg for conventional solid-phase extraction (SPE), lower than those usually stipulated by government legislation in food matrices. For LTP-dSPE, the matrx effect (ME) ranged from -16.3 to -68.6 %, lower than that for the SPE method, ranging from -70.0 to -92.9 %. The results showed satisfactory efficiency and precision, with recovery values ranging from 67.9 to 115.4 % for LTP-dSPE and from 62.0 to 114.8 % for conventional SPE, with relative standard deviations below 13.0 %. Notably, the proposed LTP-dSPE/ESI-IMS has been shown to be more cost-effective, easier to use, more environment-friendly, more accessible, and, most importantly, less matrix effect than the conventional method, thereby being suitably applicable to a wide range of food safety applications.

Fructus Ligustri Lucidi inhibits ferroptosis in ovariectomy­induced osteoporosis in rats via the Nrf2/HO­1 signaling pathway.

Postmenopausal osteoporosis (PMOP) has increased in prevalence in recent years, thus researchers have evaluated alternative medicine therapies. Fructus Ligustri Lucidi (FLL) can inhibit bone loss, and ferroptosis serves an important role in osteoporosis. Therefore, the present study assessed the presence of ferroptosis in PMOP and whether FLL could inhibit ferroptosis to improve bone microstructure in ovariectomized rats. Ovariectomized rats were treated with FLL (1.56 g/kg/day) for 12 weeks. Micro-CT was performed to evaluate the bone microstructure and bone mineral density. Western blotting and reverse transcription-quantitative PCR were performed to assess the relative expression levels of proteins and mRNA. Subsequently, malondialdehyde (MDA) and Fe2+ assay kits were used to quantify the MDA and Fe2+ content, respectively. The results demonstrated that ovariectomy (OVX) resulted in iron overload and the accumulation of lipid peroxide. Furthermore, the expression of key factors that inhibited ferroptosis, glutathione peroxidase 4 and solute carrier family 7 member 11 was significantly downregulated in ovariectomized rats, which was significantly reversed by FLL treatment. Furthermore, bone formation was assessed using the expression of osteogenesis-related genes, runt-related transcription factor 2 and osterix, which revealed significantly higher levels in FLL-treated rats compared with ovariectomized rats. The levels of nuclear factor erythroid 2-related factor 2 (Nrf2) and heme oxygenase-1 (HO-1) were also significantly recovered following FLL treatment. In the present study, OVX of postmenopausal osteoporotic rats was found to induce ferroptosis by enhancing lipid peroxidation and Fe2+ levels. FLL significantly suppressed ferroptosis, protected the osteogenic ability of ovariectomized rats and promoted the Nrf2/HO-1 signaling pathway.

Causal relationship between gut microbiota and glioblastoma: a two-sample Mendelian randomization study.

Background: Observational research and medical trials have suggested a connection between gut microbiota and glioblastoma, but it remains unclear if the relationship is causal. Method: A two-sample Mendelian randomization (MR) study was conducted by employing data from the MiBioGen consortium's largest genome-wide association study (n=18340) and the FinnGen consortium R8 release information (162 cases and 256,583 controls). Inverse variance weighted (IVW), weighted median estimator (WME), weighted model, MR-Egger, simple mode, and MR-PRESSO were used to determine the causal relationship between gut microbiota and glioblastoma. Reverse MR analysis was also performed on bacteria identified as causally related to glioblastoma. Results: Seven causal relationships were identified between genetic liability in the gut microbiota and glioblastoma, involving various bacterial families and genera. No significant causal effect was found on gut microbiota from glioblastoma, and no significant heterogeneity of instrumental variables (IVs) or horizontal pleiotropy was observed. Conclusion: A two-sample MR analysis reveals a causal association between the gut microbiota and glioblastoma, highlighting the need for more investigation to comprehend the processes behind this association.

Unveiling the influence of daily dietary patterns on brain cortical structure: insights from bidirectional Mendelian randomization.

Cognitive impairment is a significant concern in aging populations. This study utilized Mendelian randomization analysis to explore the impact of dietary habits and macro-nutrients on cortical structure. A bidirectional Mendelian randomization approach was employed, incorporating large-scale genetic data on dietary habits and brain cortical structure. The results did not reveal significant causal relationships between dietary factors and overall cortical structure and thickness. However, specific dietary factors showed associations with cortical structure in certain regions. For instance, fat intake affected six cortical regions, while milk, protein, fruits, and water were associated with changes in specific regions. Reverse analysis suggested that cortical thickness influenced the consumption of alcohol, carbohydrates, coffee, and fish. These findings contribute to understanding the potential mechanisms underlying the role of dietary factors in cognitive function changes and provide evidence supporting the existence of the gut-brain axis.

Gray Matter Thickness and Subcortical Nuclear Volume in Men After SARS-CoV-2 Omicron Infection.

Importance: The clinical manifestations and effects on the brain of the SARS-CoV-2 Omicron variant in the acute postinfection phase remain unclear. Objective: To investigate the pathophysiological mechanisms underlying clinical symptoms and changes to gray matter and subcortical nuclei among male patients after Omicron infection and to provide an imaging basis for early detection and intervention. Design, Setting, and Participants: In this cohort study, a total of 207 men underwent health screening magnetic resonance imaging scans between August 28 and September 18, 2022; among them, 98 provided complete imaging and neuropsychiatric data. Sixty-one participants with Omicron infection were reevaluated after infection (January 6 to 14, 2023). Neuropsychiatric data, clinical symptoms, and magnetic resonance imaging data were collected in the acute post-Omicron period, and their clinical symptoms were followed up after 3 months. Gray matter indexes and subcortical nuclear volumes were analyzed. Associations between changes in gray matter and neuropsychiatric data were evaluated with correlation analyses. Exposures: Gray matter thickness and subcortical nuclear volume change data were compared before and after Omicron infection. Main Outcomes and Measures: The gray matter indexes and subcutaneous nuclear volume were generated from the 3-dimensional magnetization-prepared rapid acquisition gradient echo and were calculated with imaging software. Results: Ninety-eight men underwent complete baseline data collection; of these, 61 (mean [SD] age, 43.1 [9.9] years) voluntarily enrolled in post-Omicron follow-up and 17 (mean [SD] age, 43.5 [10.0] years) voluntarily enrolled in 3-month follow-up. Compared with pre-Omicron measures, Beck Anxiety Inventory scores were significantly increased (median, 4.50 [IQR, 1.00-7.00] to 4.00 [IQR, 2.00-9.75]; P = .006) and depressive distress scores were significantly decreased (median, 18.00 [IQR, 16.00-20.22] to 16.00 [IQR, 15.00-19.00]; P = .003) at the acute post-Omicron follow-up. Fever, headache, fatigue, myalgia, cough, and dyspnea were the main symptoms during the post-Omicron follow-up; among the participants in the 3-month follow-up, fever (11 [64.7%] vs 2 [11.8%]; P = .01), myalgia (10 [58.8%] vs 3 (17.6%]; P = .04), and cough (12 [70.6%] vs 4 [23.5%]; P = .02) were significantly improved. The gray matter thickness in the left precuneus (mean [SD], 2.7 [0.3] to 2.6 [0.2] mm; P < .001) and right lateral occipital region (mean [SD], 2.8 [0.2] to 2.7 [0.2] and 2.5 [0.2] to 2.5 [0.2] mm; P < .001 for both) and the ratio of the right hippocampus volume to the total intracranial volume (mean [SD]. 0.003 [0.0003] to 0.003 [0.0002]; P = .04) were significantly reduced in the post-Omicron follow-up. The febrile group had reduced sulcus depth of the right inferior parietal region compared with the nonfebrile group (mean [SD], 3.9 [2.3] to 4.8 [1.1]; P = .048. In the post-Omicron period, the thickness of the left precuneus was negatively correlated with the Beck Anxiety Inventory scores (r = -0.39; P = .002; false discovery rate P = .02), and the ratio of the right hippocampus to the total intracranial volume was positively correlated with the Word Fluency Test scores (r = 0.34; P = .007). Conclusions and Relevance: In this cohort study of male patients infected with the Omicron variant, the duration of symptoms in multiple systems after infection was short. Changes in gray matter thickness and subcortical nuclear volume injury were observed in the post-Omicron period. These findings provide new insights into the emotional and cognitive mechanisms of an Omicron infection, demonstrate its association with alterations to the nervous system, and verify an imaging basis for early detection and intervention of neurological sequelae.

The diagnostic performance of machine learning based on resting-state functional magnetic resonance imaging data for major depressive disorders: a systematic review and meta-analysis.

Objective: Machine learning (ML) has been widely used to detect and evaluate major depressive disorder (MDD) using neuroimaging data, i.e., resting-state functional magnetic resonance imaging (rs-fMRI). However, the diagnostic efficiency is unknown. The aim of the study is to conduct an updated meta-analysis to evaluate the diagnostic performance of ML based on rs-fMRI data for MDD. Methods: English databases were searched for relevant studies. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) was used to assess the methodological quality of the included studies. A random-effects meta-analytic model was implemented to investigate the diagnostic efficiency, including sensitivity, specificity, diagnostic odds ratio (DOR), and area under the curve (AUC). Regression meta-analysis and subgroup analysis were performed to investigate the cause of heterogeneity. Results: Thirty-one studies were included in this meta-analysis. The pooled sensitivity, specificity, DOR, and AUC with 95% confidence intervals were 0.80 (0.75, 0.83), 0.83 (0.74, 0.82), 14.00 (9, 22.00), and 0.86 (0.83, 0.89), respectively. Substantial heterogeneity was observed among the studies included. The meta-regression showed that the leave-one-out cross-validation (loocv) (sensitivity: p < 0.01, specificity: p < 0.001), graph theory (sensitivity: p < 0.05, specificity: p < 0.01), n > 100 (sensitivity: p < 0.001, specificity: p < 0.001), simens equipment (sensitivity: p < 0.01, specificity: p < 0.001), 3.0T field strength (Sensitivity: p < 0.001, specificity: p = 0.04), and Beck Depression Inventory (BDI) (sensitivity: p = 0.04, specificity: p = 0.06) might be the sources of heterogeneity. Furthermore, the subgroup analysis showed that the sample size (n > 100: sensitivity: 0.71, specificity: 0.72, n < 100: sensitivity: 0.81, specificity: 0.79), the different levels of disease evaluated by the Hamilton Depression Rating Scale (HDRS/HAMD) (mild vs. moderate vs. severe: sensitivity: 0.52 vs. 0.86 vs. 0.89, specificity: 0.62 vs. 0.78 vs. 0.82, respectively), the depression scales in patients with comparable levels of severity. (BDI vs. HDRS/HAMD: sensitivity: 0.86 vs. 0.87, specificity: 0.78 vs. 0.80, respectively), and the features (graph vs. functional connectivity: sensitivity: 0.84 vs. 0.86, specificity: 0.76 vs. 0.78, respectively) selected might be the causes of heterogeneity. Conclusion: ML showed high accuracy for the automatic diagnosis of MDD. Future studies are warranted to promote the potential use of these classification algorithms in clinical settings.

Sleep Traits Causally Affect the Brain Cortical Structure: A Mendelian Randomization Study.

Background: Brain imaging results in sleep deprived patients showed structural changes in the cerebral cortex; however, the reasons for this phenomenon need to be further explored. Methods: This MR study evaluated causal associations between morningness, ease of getting up, insomnia, long sleep, short sleep, and the cortex structure. Results: At the functional level, morningness increased the surface area (SA) of cuneus with global weighted (beta(b) (95% CI): 32.63 (10.35, 54.90), p = 0.004). Short sleep increased SA of the lateral occipital with global weighted (b (95% CI): 394.37(107.89, 680.85), p = 0.007. Short sleep reduced cortical thickness (TH) of paracentral with global weighted (OR (95% CI): -0.11 (-0.19, -0.03), p = 0.006). Short sleep reduced TH of parahippocampal with global weighted (b (95% CI): -0.25 (-0.42, -0.07), p = 0.006). No pleiotropy was detected. However, none of the Bonferroni-corrected p values of the causal relationship between cortical structure and the five types of sleep traits met the threshold. Conclusions: Our results potentially show evidence of a higher risk association between neuropsychiatric disorders and not only paracentral and parahippocampal brain areas atrophy, but also an increase in the middle temporal zone. Our findings shed light on the associations of cortical structure with the occurrence of five types of sleep traits.

Correlation between cerebral cortex changes and clinical features in patients with neuromyelitis optica spectrum disorder with normal-appearing brain tissue: a case-control study.

Neuromyelitis optica spectrum disorder (NMOSD) is an inflammatory demyelinating disease of the central nervous system. However, whether and how cortical changes occur in NMOSD with normal-appearing brain tissue, or whether any cortical changes correlate with clinical characteristics, is not completely clear. The current study recruited 43 patients with NMOSD who had normal-appearing brain tissue and 45 healthy controls matched for age, sex, and educational background from December 2020 to February 2022. A surface-based morphological analysis of high-resolution T1-weighted structural magnetic resonance images was used to calculate the cortical thickness, sulcal depth, and gyrification index. Analysis showed that cortical thickness in the bilateral rostral middle frontal gyrus and left superior frontal gyrus was lower in the patients with NMOSD than in the control participants. Subgroup analysis of the patients with NMOSD indicated that compared with those who did not have any optic neuritis episodes, those who did have such episodes exhibited noticeably thinner cortex in the bilateral cuneus, superior parietal cortex, and pericalcarine cortex. Correlation analysis indicated that cortical thickness in the bilateral rostral middle frontal gyrus was positively correlated with scores on the Digit Symbol Substitution Test and negatively correlated with scores on the Trail Making Test and the Expanded Disability Status Scale. These results are evidence that cortical thinning of the bilateral regional frontal cortex occurs in patients with NMOSD who have normal-appearing brain tissue, and that the degree of thinning is correlated with clinical disability and cognitive function. These findings will help improve our understanding of the imaging characteristics in NMOSD and their potential clinical significance.

Single-cell sequencing of immune cells after marathon and symptom-limited cardiopulmonary exercise.

Vigorous-intensity leisure-time physical activity, such as marathon, has become increasingly popular, but its effect on immune functions and health is poorly understood. Here, we performed scRNA-seq analysis of peripheral blood mononuclear cells (PBMCs) after a bout of symptom-limited cardiopulmonary exercise (CPX) test or marathon. Time-series single-cell analysis revealed the detailed series of landscapes of immune cells in response to short and long vigorous-intensity activities. Reduction of effective T cells was observed with the cell migration and motility pathways enriched in circulation following marathon. Baseline values of PBMCs abundance were reached around 1 h after CPX and 24 h following marathon, but longer time was required for expression recovery of cytotoxicity genes. The ratio of effector/naive T cells was found to change uniformly among the participants and could serve as a better indicator for exercise intensity than the CD4+/CD8+ T cell ratio. Moreover, we identified time-dependent monocyte state transitions after marathon.

Alteration of the gut microbiome and correlated metabolism in a rat model of long-term depression.

Objective: This study aims to investigate the composition and function of the gut microbiome in long-term depression using an 8-week chronic unpredictable mild stress (CUMS) rat model. Materials and methods: Animals were sacrificed after either 4 weeks or 8 weeks under CUMS to mimic long-term depression in humans. The gut microbiome was analyzed to identify potential depression-related gut microbes, and the fecal metabolome was analyzed to detect their functional metabolites. The correlations between altered gut microbes and metabolites in the long-term depression rats were explored. The crucial metabolic pathways related to long-term depression were uncovered through enrichment analysis based on these gut microbes and metabolites. Results: The microbial composition of long-term depression (8-week CUMS) showed decreased species richness indices and different profiles compared with the control group and the 4-week CUMS group, characterized by disturbance of Alistipes indistinctus, Bacteroides ovatus, and Alistipes senegalensis at the species level. Additionally, long-term depression was associated with disturbances in fecal metabolomics. D-pinitol was the only increased metabolite in the 8-week CUMS group among the top 10 differential metabolites, while the top 3 decreased metabolites in the long-term depression rats included indoxyl sulfate, trimethylaminen-oxide, and 3 alpha,7 alpha-dihydroxy-12-oxocholanoic acid. The disordered fecal metabolomics in the long-term depression rats mainly involved the biosynthesis of pantothenate, CoA, valine, leucine and isoleucine. Conclusion: Our findings suggest that the gut microbiome may participate in the long-term development of depression, and the mechanism may be related to the regulation of gut metabolism.

Rapid and Accurate Detection of SARS-CoV-2 Using an iPad-Controlled, High-Throughput, Portable, and Multiplex Hive-Chip Platform (HiCube).

Rapid and accurate detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is one of the most effective measures to control the coronavirus disease 2019 (COVID-19) pandemic. However, there is still lack of an ideal detection platform capable of high sample throughput, portability, and multiplicity. Herein, by combining Hive-Chip (capillary microarray) and reverse transcriptional loop-mediated isothermal amplification (RT-LAMP), we developed an iPad-controlled, high-throughput (48 samples at one run), portable (smaller than a backpack), multiplex (monitoring 8 gene fragments in one reaction), and real-time detection platform for SARS-CoV-2 detection. This platform is composed of a portable Hive-Chip device (HiCube; 32.7 × 29.7 × 20 cm, 5 kg), custom-designed software, and optimized Hive-Chips. RT-LAMP primers targeting seven SARS-CoV-2 genes (S, E, M, N, ORF1ab, ORF3a, and ORF7a) and one positive control (human RNase P) were designed and prefixed in the Hive-Chip. On-chip RT-LAMP showed that the limit of detection (LOD) of SARS-CoV-2 synthetic RNAs is 1 copy/µL, and there is no cross-reaction among different target genes. The platform was validated by 100 clinical samples of SARS-CoV-2, and the results were highly consistent with those of the traditional real-time PCR assay. In addition, on-chip detection of 6 other respiratory pathogens showed no cross-reactivity. Overall, our platform has great potential for fast, accurate, and on-site detection of SARS-CoV-2.

Diosgenin reduces bone loss through the regulation of gut microbiota in ovariectomized rats.

Diosgenin (DIO) is an aglycone of steroid saponins acquired from plants, including Dioscorea alata, Smilax China, and Trigonella foenum graecum, acting as an anti-osteoporosis, anti-diabetic, anti-hyperlipidemic, anti-inflammatory. Recent studies have demonstrated that DIO reduces bone loss. This study aimed to investigate the effects of DIO on the gut microbiota (GM) of ovariectomized (OVX) osteoporotic rats. Female Sprague-Dawley rats were randomly divided into sham operation (sham + vehicle group) or ovariectomy. For 12 weeks, OVX rats were treated using a vehicle (OVX + vehicle group) and DIO (OVX + DIO group). Subsequently, ELISA was conducted to determine serum estradiol levels, micro-CT scanning was performed to evaluate bone quality, and feces were collected for metagenomics sequencing to examine the structure and function of GM. Raw reads were filtered to remove chimera sequences. Operational taxonomic units (OTUs) were clustered in the filtered reads. A Venn diagram analysis was conducted to study the common and unique OTUs in the sham + vehicle, OVX + vehicle, and OVX + DIO groups. LEfSe analysis was conducted to evaluate the specific GM of the three groups. The GM functions were analyzed using the KEGG and CAZy databases. After a 12-week treatment, DIO administration prevented OVX-induced weight gain and increased the estradiol levels. DIO treatment improved the bone microstructure and structural parameters of rat tibias. Metagenomics sequencing results identified 1139, 1207, and 1235 operational taxonomic units (OTUs) in the sham + vehicle, OVX + vehicle, and OVX + DIO groups, respectively. The percentage of common OTUs was 41.2%. Treatment with DIO restored the composition of GM in OVX rats by increasing the abundance of Coriobacteriia Adlercreutzia, Romboutsia, and Romboutsia_idealis and reducing the abundance of Betaproteobacteria, Gammaproteobacteria, Methanobacteria, Bacteroides, Phocaeicola, Alistipes, Bacteroids_uniformis, Bacteroids_xylanisolvens. The anti-osteoporosis effect of DIO can be regulated through environmental information processing, organismal Systems, Cellular Processes, human diseases, metabolism, and genetic information processing. Meanwhile, treatment with DIO improved GM homeostasis by increasing the metabolism of carbohydrates, other amino acids, and glycans and reducing translation, energy metabolism, and nucleotide metabolism. DIO can reduce bone loss by regulating the structural composition and function of GM, a novel strategy for preventing osteoporosis.

Effects of donkey milk on UVB-induced skin barrier damage and melanin pigmentation: A network pharmacology and experimental validation study.

Introduction: Dairy products have long been regarded as a controversial nutrient for the skin. However, a clear demonstration of donkey milk (DM) on skincare is required. Methods: In this study, spectrum and chemical component analyses were applied to DM. Then, the effects of DM on UVB-induced skin barrier damage and melanin pigmentation were first evaluated in vitro and in vivo. Cell survival, animal models, and expression of filaggrin (FLG) were determined to confirm the effect of DM on UVB-induced skin barrier damage. Melanogenesis and tyrosinase (TYR) activity were assessed after UVB irradiation to clarify the effect of DM on whitening activities. Further, a network pharmacology method was applied to study the interaction between DM ingredients and UVB-induced skin injury. Meanwhile, an analysis of the melanogenesis molecular target network was developed and validated to predict the melanogenesis regulators in DM. Results: DM was rich in cholesterols, fatty acids, vitamins and amino acids. The results of evaluation of whitening activities in vitro and in vivo indicated that DM had a potent inhibitory effect on melanin synthesis. The results of effects of DM on UVB­induced skin barrier damage indicated that DM inhibited UVB-induced injury and restored skin barrier function via up-regulation expression of FLG (filaggrin). The pharmacological network of DM showed that DM regulated steroid biosynthesis and fatty acid metabolism in keratinocytes and 64 melanin targets which the main contributing role of DM might target melanogenesis, cell adhesion molecules (CAMs), and Tumor necrosis factor (TNF) pathway. Discussion: These results highlight the potential use of DM as a promising agent for whitening and anti-photoaging applications.

A fully integrated nucleic acid analysis system for multiplex detection of genetic polymorphisms related to folic acid metabolism.

A sufficient intake of folic acid is essential during pregnancy, but several genetic polymorphisms reduce its absorption, threaten the lives of pregnant women and cause congenital disabilities in newborns. Traditional laboratory detection of genetic variants related to folic acid metabolism is time-consuming and labor-intensive. Microfluidics-based molecular diagnosis integrates sample pre-processing and nucleic acid amplification on-chip to achieve rapid, sensitive, high-throughput, and automated detection. Here, we developed a fully integrated microfluidic system for the detection of genetic polymorphisms related to folic acid metabolism in a "sample in-answer out" style. The system consists of nucleic acid extraction and amplification modules. During nucleic acid extraction, blood cells are lysed, and DNA is captured and eluted through a silica-gel membrane. After that, multiple gene loci are detected using loop-mediated isothermal amplification (LAMP) and the color of the reaction chamber indicates whether genetic mutations are present. The experimental results demonstrate that the system can accurately detect gene polymorphisms associated with folic acid metabolism in blood samples with high sensitivity and no cross-contamination between chambers. The blood samples of five patients were tested for mutant alleles on this system, and the test results were consistent with qPCR and DNA sequencing observations. The operation is fully automated, and the detection is completed in approximately 70 minutes. The proposed system has great potential in prenatal diagnosis and other types of nucleic acid detection.

Dynamic white matter changes in recovered COVID-19 patients: a two-year follow-up study.

Background and purpose: Long COVID with regard to the neurological system deserves more attention, as a surge of treated patients are being discharged from the hospital. As the dynamic changes in white matter after two years remain unknown, this characteristic was the focus of this study. Methods: We investigated 17 recovered COVID-19 patients at two years after discharge. Diffusion tensor imaging, neurite orientation dispersion and density imaging were performed to identify white matter integrity and changes from one to two years after discharge. Data for 13 revisited healthy controls were collected as a reference. Subscales of the Wechsler Intelligence scale were used to assess cognitive function. Repeated-measures ANOVA was used to detect longitudinal changes in 17 recovered COVID-19 patients and 13 healthy controls after one-year follow-up. Correlations between diffusion metrics, cognitive function, and other clinical characteristics (i.e., inflammatory factors) were also analyzed. Results: Longitudinal analysis showed the recovery trends of large-scale brain regions, with small-scale brain region deterioration from one year to two years after SARS-CoV-2 infection. However, persistent white matter abnormalities were noted at two years after discharge. Longitudinal changes of cognitive function showed no group difference. But cross-sectional cognitive difference between recovered COVID-19 patients and revisited HCs was detected. Inflammation levels in the acute stage correlated positively with white matter abnormalities and negatively with cognitive function. Moreover, the more abnormal the white matter was at two years, the greater was the cognitive deficit present. Conclusion: Recovered COVID-19 patients showed longitudinal recovery trends of white matter. But also had persistent white matter abnormalities at two years after discharge. Inflammation levels in the acute stage may be considered predictors of cognition and white matter integrity, and the white matter microstructure acts as a biomarker of cognitive function in recovered COVID-19 patients. These findings provide an objective basis for early clinical intervention.