Chitinases as a potential diagnostic and prognostic biomarker for amyotrophic lateral sclerosis: a systematic review and meta-analysis.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by the degeneration of motor neurons, and there is currently a lack of reliable diagnostic biomarkers. This meta-analysis aimed to evaluate CHIT1, CHI3L1, and CHI3L2 levels in the cerebrospinal fluid (CSF) or blood and their diagnostic potential in ALS patients. A systematic, comprehensive search was performed of peer-reviewed English-language articles published before April 1, 2023, in PubMed, Scopus, Embase, Cochrane Library, and Web of Science. After a thorough screening, 13 primary articles were included, and their chitinases-related data were extracted for systematic review and meta-analysis. In ALS patients, the CSF CHIT1 levels were significantly elevated compared to controls with healthy control (HC) (SMD, 1.92; 95% CI, 0.78 - 3.06; P < 0.001). CHIT1 levels were elevated in the CSF of ALS patients compared to other neurodegenerative diseases (ONDS) control (SMD, 0.74; 95% CI, 0.22 - 1.27; P < 0.001) and exhibited an even more substantial increase when compared to ALS-mimicking diseases (AMDS) (SMD, 1.15; 95% CI, 0.35 - 1.94, P < 0.001). Similarly, the CSF CHI3L1 levels were significantly higher in ALS patients compared to HC (SMD, 3.16; 95% CI, 1.26 - 5.06, P < 0.001). CHI3L1 levels were elevated in the CSF of ALS patients compared to ONDS (SMD, 0.75; 95% CI, 0.32 - 1.19; P = 0.017) and exhibited a more pronounced increase when compared to AMDS (SMD, 1.92; 95% CI, 0.41 - 3.42; P < 0.001). The levels of CSF chitinases in the ALS patients showed a significant increase, supporting the role of CSF chitinases as diagnostic biomarkers for ALS.

The mediating role of children's intergenerational support in association between grandparenting and cognitive function among middle-aged and older Chinese: findings from the CHARLS cohort study.

OBJECTIVES: With the world's population increasing in age, there has been a significant rise in the prevalence of cognitive impairment and dementia among individuals. This study aims to investigate the association between grandparenting and cognitive function among middle-aged and older Chinese using data from 2011 to 2018 China Health and Retirement Longitudinal Study (CHARLS). Additionally, the study seeks to explore the potential mediating effect of intergenerational support from children on this relationship, using data from the CHARLS 2011 database. METHODS: 5254 participants were recruited at the baseline survey in CHARLS 2011. Subsequently, a follow-up survey was conducted over 8 years, from CHARLS 2011 to 2018, with 1472 individuals completing the follow-up survey. The CHARLS included surveys on grandparenting and cognitive assessments. Grandparenting was categorized as yes and no. The assessment of cognitive function involved the evaluation of episodic memory and mental intactness. The present study used cross-sectional and longitudinal analyses to examine the relationship between grandparenting and cognitive function. The bootstrap method assessed the mediating effect of children's intergenerational support. RESULTS: The results of both cross-sectional and longitudinal studies indicated a positive association between grandparenting and cognitive function in middle-aged and older Chinese (B = 0.138, p < 0.05; B = 0.218, p < 0.05). Children's emotional and economic support played intermediary roles between grandparenting and cognitive function. CONCLUSION: The results emphasized the significance of policymakers considering the consequences of intergenerational care and family support when formulating and executing social service policies targeted at the middle-aged and older population in China.

Effectiveness of continuity of care in reducing depression symptoms in elderly: A systematic review and meta-analysis.

BACKGROUND: Depression affects 10%-20% of older adults worldwide. The course of late-life depression (LLD) is often chronic, with a poor long-term prognosis. Lower treatment adherence, stigma, and suicide risk lead to significant challenges in the continuity of care (COC) for patients with LLD. Elderly patients with chronic diseases can benefit from COC. As a common chronic disease of the elderly, whether depression can also benefit from COC has not been systematically reviewed. METHODS: Systematic literature search in Embase, Cochrane Library, Web of Science, Ovid, PubMed and Medline. Randomized Controlled Trials (RCTs) on the intervention effects of COC and LLD, published on 12 April 2022, were selected. Two independent researchers made research choices based on consensus. An RCT with COC as an intervention measure for the elderly with depression 60 years old was the inclusion criteria. RESULTS: A total of 10 RCTs involving 1557 participants were identified in this study. The findings showed that: (1) COC significantly reduced depressive symptoms compared to usual care (standardized mean difference [SMD] = -0.47, 95% confidence interval: -0.63 to -0.31), with the best improvement at 3- to 6-month follow-up; (2) The reduction in depressive symptoms was more pronounced for patients with comorbid chronic conditions with LLD (SMD = -0.93, 95% CI: -1.18 to -0.68); (3) COC was more effective than other regions for LLD in Europe and the Americas (SMD = -0.84, 95% CI: -1.07 to -0.61); and (4) COC had a positive impact on the quality of life of patients with LLD (SMD = 0.21, 95% CI: 0.02-0.40). LIMITATIONS: The included studies included several multi-component interventions with widely varying methods. Therefore, it was almost impossible to analyze which of these interventions had an impact on the assessed outcomes. CONCLUSIONS: This meta-analysis shows that COC can significantly reduce depressive symptoms and improve quality of life in patients with LLD. However, when treating and caring for patients with LLD, health care providers should also pay attention to timely adjustments of intervention plans according to follow-up, synergistic interventions for multiple co-morbidities, and actively learning from advanced COC programs at home and abroad to improve the quality and effectiveness of services.

Association between pro-inflammatory diet and liver cancer risk: a systematic review and meta-analysis.

OBJECTIVE: This systematic review aimed to investigate the association between dietary inflammatory potential and liver cancer to provide evidence regarding scientific dietary health education. DESIGN: Systematic review and meta-analysis. SETTING: A comprehensive literature review was conducted to identify case-control or cohort studies that involved dietary inflammation index (DII)/empirical dietary inflammation pattern (EDIP) and liver cancer in PubMed, EMBASE, Cochrane, and Web of Science databases. Using a combination of DII/EDIP and liver cancer as the search terms, the associations between DII/EDIP and liver cancer were then assessed. PARTICIPANTS: Three case-control studies and two cohort studies were brought into the meta-analysis, with 225 713 enrolled participants. RESULTS: Meta-analysis of categorical variables showed that DII/EDIP in the highest category increased the risk of liver cancer compared to DII/EDIP in the lowest category (relative risk (RR) = 2·35; 95 % CI 1·77, 3·13; P = 0·000) and with low heterogeneity across studies (I2 = 40·8 %, P = 0·119). Meta-analysis of continuous variables showed that significant positive association between liver cancer and DII/EDIP scores (RR = 1·24; 95 % CI 1·09, 1·40; P = 0·001), and no heterogeneity (I² = 0·0 %, P = 0·471). Stratified according to the study design, there was a significant positive association between liver cancer and DII/EDIP scores in both cohort studies (RR = 2·16; 95 % CI 1·51, 3·07; P = 0·000) and case-control studies (RR = 2·75; 95 % CI 1·71, 4·41; P = 0·000). CONCLUSION: The higher the DII/EDIP score, the higher the risk of liver cancer. This finding may have prominent implications for the general population.

Structure determination of noncanonical RNA motifs guided by ¹H NMR chemical shifts.

Structured noncoding RNAs underlie fundamental cellular processes, but determining their three-dimensional structures remains challenging. We demonstrate that integrating ¹H NMR chemical shift data with Rosetta de novo modeling can be used to consistently determine high-resolution RNA structures. On a benchmark set of 23 noncanonical RNA motifs, including 11 'blind' targets, chemical-shift Rosetta for RNA (CS-Rosetta-RNA) recovered experimental structures with high accuracy (0.6-2.0 Å all-heavy-atom r.m.s. deviation) in 18 cases.

Tyrosine kinase inhibitors induce mesenchymal stem cell-mediated resistance in BCR-ABL+ acute lymphoblastic leukemia.

Tyrosine kinase inhibitors (TKIs) are used as a frontline therapy for BCR-ABL(+) acute lymphoblastic leukemia (ALL). However, resistance to TKI therapy arises rapidly, and its underlying molecular mechanisms are poorly understood. In this study, we identified a novel cascade of events initiated by TKIs and traversing through mesenchymal stem cells (MSCs) to leukemic cells, leading to resistance. MSCs exposed to TKIs acquired a new functional status with the expression of genes encoding for chemo-attractants, adhesion molecules, and prosurvival growth factors, and this priming enabled leukemic cells to form clusters underneath the MSCs. This cluster formation was associated with the protection of ALL cells from therapy as leukemic cells switched from BCR-ABL signaling to IL-7R/Janus kinase signaling to survive in the MSC milieu. Our findings illustrate a novel perspective in the evolution of TKI resistance and provide insights for advancing the treatment of BCR-ABL(+) ALL.

Error removal in microchip-synthesized DNA using immobilized MutS.

The development of economical de novo gene synthesis methods using microchip-synthesized oligonucleotides has been limited by their high error rates. In this study, a low-cost, effective and improved-throughput (up to 32 oligos per run) error-removal method using an immobilized cellulose column containing the mismatch binding protein MutS was produced to generate high-quality DNA from oligos, particularly microchip-synthesized oligonucleotides. Error-containing DNA in the initial material was specifically retained on the MutS-immobilized cellulose column (MICC), and error-depleted DNA in the eluate was collected for downstream gene assembly. Significantly, this method improved a population of synthetic enhanced green fluorescent protein (720 bp) clones from 0.93% to 83.22%, corresponding to a decrease in the error frequency of synthetic gene from 11.44/kb to 0.46/kb. In addition, a parallel multiplex MICC error-removal strategy was also evaluated in assembling 11 genes encoding ∼21 kb of DNA from 893 oligos. The error frequency was reduced by 21.59-fold (from 14.25/kb to 0.66/kb), resulting in a 24.48-fold increase in the percentage of error-free assembled fragments (from 3.23% to 79.07%). Furthermore, the standard MICC error-removal process could be completed within 1.5 h at a cost as low as $0.374 per MICC.

Rapid ethanol production at elevated temperatures by engineered thermotolerant Kluyveromyces marxianus via the NADP(H)-preferring xylose reductase-xylitol dehydrogenase pathway.

Conversion of xylose to ethanol by yeasts is a challenge because of the redox imbalances under oxygen-limited conditions. The thermotolerant yeast Kluyveromyces marxianus grows well with xylose as a carbon source at elevated temperatures, but its xylose fermentation ability is weak. In this study, a combination of the NADPH-preferring xylose reductase (XR) from Neurospora crassa and the NADP(+)-preferring xylitol dehydrogenase (XDH) mutant from Scheffersomyces stipitis (Pichia stipitis) was constructed. The xylose fermentation ability and redox balance of the recombinant strains were improved significantly by over-expression of several downstream genes. The intracellular concentrations of coenzymes and the reduced coenzyme/oxidized coenzyme ratio increased significantly in these metabolic strains. The byproducts, such as glycerol and acetic acid, were significantly reduced by the disruption of glycerol-3-phosphate dehydrogenase (GPD1). The resulting engineered K. marxianus YZJ088 strain produced 44.95 g/L ethanol from 118.39 g/L xylose with a productivity of 2.49 g/L/h at 42 °C. Additionally, YZJ088 realized glucose and xylose co-fermentation and produced 51.43 g/L ethanol from a mixture of 103.97 g/L xylose and 40.96 g/L glucose with a productivity of 2.14 g/L/h at 42 °C. These promising results validate the YZJ088 strain as an excellent producer of ethanol from xylose through the synthetic xylose assimilation pathway.

Characterizing yeast promoters used in Kluyveromyces marxianus.

Fermentation at higher temperatures can potentially reduce the cooling cost in large-scale fermentation and reduce the contamination risk. Thus, the thermotolerant yeast, Kluyveromyces marxianus, which can grow and ferment at elevated temperatures, is a promising biotechnological tool for future applications. However, the promoters used in K. marxianus are not well characterized, especially at elevated temperatures, which is important in efficient metabolic pathway construction. In this study, six constitutive promoters (P(TDH3), P(PGK), and P(ADH1) from both Saccharomyces cerevisiae and K. marxianus) were evaluated in K. marxianus through the heterologous expression of the KlLAC4, GUSA, and SH BLE genes at various temperatures, with various carbon sources and oxygen conditions. The expression was evaluated at the transcription and protein level using real-time PCR and protein activity determination to eliminate the effect of heterologous protein stability. While the transcription of all the promoters decreased at higher temperatures, the order of their promoting strength at various temperatures with glucose as the carbon source was P(KmPGK) > P(KmTDH3) > P(ScPGK) > P(ScTDH3) > P(KmADH1) > P(ScADH1). When glycerol or xylose was supplied as the carbon source at 42 °C, the order of promoter strength was P(KmPGK) > P(ScPGK) > P(KmADH1) > P(ScADH1) > P(ScTDH3) > P(KmTDH3). The promoter activity of P TDH3 decreased significantly, while the promoter activity of both of the P(ADH1) promoters increased. Oxygen conditions had non-significant effect. The results of this study provide important information for fine-tuned pathway construction for the metabolic engineering of K. marxianus.

Association between dietary vitamin A intake and risk of cardiometabolic multimorbidity.

The association between vitamin A and single cardiometabolic diseases has been extensively studied, but the relationship between dietary vitamin A intake and the risk of cardiometabolic multimorbidity (CMM) has not been studied. Therefore, the present study was conducted to explore the association with CMM risk by analyzing different sources of vitamin A. This study utilized 13,603 subjects aged ≥ 18 years from 1997 to 2015 from the China Health and Nutrition Survey (CHNS). Dietary intake was calculated from 3 consecutive 24-h dietary recalls combined with a house hold food inventory. CMM is defined as the development of at least two cardiometabolic diseases. After a median follow-up of 9.0 years, there were 1050 new cases of CMM. The risk of CMM was significantly lower in those with higher vitamin A intake (Q1 vs Q5 HR 0.66, 95% CI 0.54-0.81). ß-carotene (Q1 vs Q5 HR 0.82, 95% CI 0.66-1.02) and retinol (Q1 vs Q5 HR 0.59, 95% CI 0.48-0.73) intake had a similarly negative correlation. Using restricted cubic spline found an L-shaped relationship between retinol intake and CMM (p non-linear < 0.001). Negative associations were also found in specific CMD groups (hypertension, cardiovascular disease, stroke and diabetes). Dietary intake of vitamin A was negatively associated with CMM risk, and this protective effect was more pronounced in patients with cardiovascular disease. There was an L-shaped association between retinol intake and CMM risk.

Association between Dietary Total Vitamin A, ß-carotene, and Retinol Intake and Risk of cardiometabolic multimorbidity: Results from the China Health and Nutrition Survey, 1997-2015.

Background: The association between vitamin A and single cardiometabolic diseases has been extensively studied, but the relationship between dietary vitamin A intake and the risk of cardiometabolic multimorbidity (CMM) has not been studied. Therefore, the present study was conducted to explore the association with CMM risk by analyzing different sources of vitamin A. Methods: This study utilized 13,603 subjects aged ≥ 18 years from 1997-2015 from the China Health and Nutrition Survey (CHNS). Dietary intake was calculated from 3 consecutive 24-h dietary recalls combined with a house hold food inventory. CMM is defined as the development of at least two cardiometabolic diseases. Results: After a median follow-up of 9.1 years, there were 1050 new cases of CMM. The risk of CMM was significantly lower in those with higher vitamin A intake (Q1 vs Q5 HR 0.66, 95% CI 0.54-0.81). ß-carotene (Q1 vs Q5 HR 0.82, 95% CI 0.66-1.02) and retinol (Q1 vs Q5 HR 0.59, 95%CI 0.48-0.73) intake had a similarly negative correlation. Using restricted cubic spline found an L-shaped relationship between retinol intake and CMM (p non-linear < 0.001). In subgroup analyses, protective effects were stronger for participants aged ≥ 44 years (HR 0.72, 95%CI 0.57-0.92) and for the female group (HR 0.62, 95%CI 0.45-0.84). Conclusion: Dietary vitamin A was a protective factor for CMM, and this effect was stronger in age ≥ 44 years and in the female group. There was a ceiling effect on the protective effect of retinol intake on the risk of CMM.

Effectiveness of Telecare Interventions on Depression Symptoms Among Older Adults: Systematic Review and Meta-Analysis.

BACKGROUND: Depression is the most common psychiatric disorder among older adults. Despite the effectiveness of pharmacological and psychological therapies, many patients with late-life depression (LLD) are unable to access timely treatment. Telecare has been shown to be effective in addressing patients' psychosocial issues, while its effectiveness in serving patients with LLD remains unclear. OBJECTIVE: This study aimed to evaluate the effectiveness of telecare in reducing depression and anxiety symptoms and improving quality of life (QoL) in patients with LLD. METHODS: Databases including the Cochrane Library, Web of Science, PubMed, Embase, and EBSCO were searched for randomized controlled trials (RCTs) evaluating the effectiveness of telecare for LLD from database establishment to December 28, 2022. RESULTS: A total of 12 RCTs involving 1663 participants were identified in this study. The meta-analysis showed that (1) telecare significantly reduced depressive symptoms in patients with LLD compared to those in usual care (UC; standardized mean difference [SMD]=-0.46, 95% CI -0.53 to -0.38; P<.001), with the best improvement observed within 3 months of intervention (SMD=-0.72, 95% CI -1.16 to -0.28; P<.001); (2) other scales appeared more effective than the Patient Health Questionnaire-9 for LLD in telecare interventions (SMD=-0.65, 95% CI -0.96 to -0.35; P<.001); (3) telecare was more effective than telephone-based interventions for remote monitoring of LLD (SMD=-1.13, 95% CI -1.51 to -0.76; P<.001); (4) the reduction of depressive symptoms was more pronounced in patients with LLD with chronic conditions (SMD=-0.67, 95% CI -0.89 to -0.44; P<.001); (5) telecare was more effective for LLD in Europe and the Americas than in other regions (SMD=-0.73, 95% CI -0.99 to -0.47; P<.001); (6) telecare significantly reduced anxiety symptoms in patients with LLD (SMD=-0.53, 95% CI -0.73 to -0.33; P=.02); and (7) there was no significant improvement in the psychological components of QoL in patients with LLD compared to those receiving UC (SMD=0.30, 95% CI 0.18-0.43; P=.80). CONCLUSIONS: Telecare is a promising modality of care for treatment, which can alleviate depression and anxiety symptoms in patients with LLD. Continued in-depth research into the effectiveness of telecare in treating depression could better identify where older patients would benefit from this intervention.

Association between indoor air pollution and depression: a systematic review and meta-analysis of cohort studies.

OBJECTIVES: Incomplete combustion of solid fuel and exposure to secondhand smoke (SHS) are the primary causes of indoor air pollution (IAP), potentially leading to detrimental effects on individual mental health. However, current evidence regarding the association between IAP and depression remains inconclusive. This study aims to systematically investigate the evidence regarding the association between IAP and the risk of depression. DESIGN: Systematic review and meta-analysis of cohort studies. DATA SOURCES: Two independent reviewers searched PubMed, the Cochrane Library, Web of Science and EMBASE for available studies published up to 13 January 2024. ELIGIBILITY CRITERIA: We included all cohort studies published in English that aimed to explore the relationship between IAP from solid fuel use and SHS exposure and the risk of depression. DATA EXTRACTION AND SYNTHESIS: Two independent reviewers extracted data and assessed the risk of bias. The association between IAP and depression was calculated using pooled relative risk (RR) with 95% CIs. Heterogeneity was assessed using the I2 value, and the effect estimates were pooled using fixed-effects or random-effects models depending on the results of homogeneity analysis. RESULTS: We included 12 articles with data from 61 217 participants. The overall findings demonstrated a significant association between IAP exposure and depression (RR=1.22, 95% CI: 1.13 to 1.31), although with substantial heterogeneity (I2=75%). Subgroup analyses based on pollutant type revealed that IAP from solid fuel use was associated with a higher risk of depression (RR=1.20, 95% CI: 1.13 to 1.26; I2=62%; 5 studies, 36 768 participants) than that from SHS exposure (RR=1.11, 95% CI: 0.87 to 1.41; I2=80%; 7 studies, 24 449 participants). In terms of fuel use, the use of solid fuel for cooking (RR: 1.23, 95% CI: 1.16 to 1.31; I2=58%; 4 studies, 34 044 participants) and heating (RR 1.15, 95% CI: 1.04 to 1.27; I2=65%; 3 studies, 24 874 participants) was associated with increased depression risk. CONCLUSIONS: The findings from this systematic review and meta-analysis of cohort studies indicated an association between exposure to IAP and depression. PROSPERO REGISTRATION NUMBER: CRD42022383285.

Association between dietary inflammatory index and gallstones in US adults.

Introduction: Previous studies have found that diet's inflammatory potential is related to various diseases. However, little is known about its relationship with gallstones. The present study aims to investigate the relationship between dietary inflammatory index (DII) and gallstones. Methods: Data were obtained from the 2003-2020 National Health and Nutrition Examination Survey (NHANES). We used the nearest neighbor propensity score matching (PSM) with a ratio of 1:1 to reduce selection bias. Logistic regression models estimated the association between DII and gallstones. The non-linear relationship was explored with restricted cubic splines (RCS). BMI subgroup stratification was performed to explore further the connection between DII and gallstones in different populations. Results: 10,779 participants were included. Before and after PSM, gallstone group individuals had higher DII scores than non-gallstone group individuals (p < 0.05). Matched logistic regression analysis showed that DII scores were positively correlated with gallstone risk (adjusted OR = 1.14, 95% CI 1.01, 1.29). The stratified analysis showed that this association was stronger in overweight or obese people (adjusted OR = 1.18, 95% CI 1.03, 1.34). RCS analysis suggested that DII and gallstones showed a "J"-shaped non-linear dose-response relationship (p non-linear <0.001). Conclusion: Higher DII score is positively associated with the risk of gallstones, particularly in overweight or obese population, and this relationship is a "J"-shaped non-linear relationship. These results further support that avoiding or reducing a pro-inflammatory diet can be an intervention strategy for gallstone management, particularly in the overweight or obese population.

Higher remnant cholesterol is associated with an increased risk of amnestic mild cognitive impairment: a community-based cross-sectional study.

Background and aims: Amnestic mild cognitive impairment (aMCI) is the most common subtype of MCI, which carries a significantly high risk of transitioning to Alzheimer's disease. Recently, increasing attention has been given to remnant cholesterol (RC), a non-traditional and previously overlooked risk factor. The aim of this study was to explore the association between plasma RC levels and aMCI. Methods: Data were obtained from Brain Health Cognitive Management Team in Wuhan (https://hbtcm.66nao.com/admin/). A total of 1,007 community-dwelling elders were recruited for this project. Based on ten tools including general demographic data, cognitive screening and some exclusion scales, these participants were divided into the aMCI (n = 401) and normal cognitive groups (n = 606). Physical examinations were conducted on all participants, with clinical indicators such as blood pressure, blood sugar, and blood lipids collected. Results: The aMCI group had significantly higher RC levels compared to the normal cognitive group (0.64 ± 0.431 vs. 0.52 ± 0.447 mmol/L, p < 0.05). Binary logistics regression revealed that occupation (P<0.001, OR = 0.533, 95%CI: 0.423-0.673) and RC (p = 0.014, OR = 1.477, 95% CI:1.081-2.018) were associated factors for aMCI. Partial correlation analysis, after controlling for occupation, showed a significant negative correlation between RC levels and MoCA scores (r = 0.059, p = 0.046), as well as Naming scores (r = 0.070, p = 0.026). ROC curve analysis demonstrated that RC levels had an independent predictive efficacy in predicting aMCI (AUC = 0.580, 95%CI: 0.544 ~ 0.615, P < 0.001). Conclusion: Higher RC levels were identified as an independent indicator for aMCI, particularly in the naming cognitive domain among older individuals. Further longitudinal studies are necessary to validate the predictive efficacy of RC.

Identification of differences in microRNA transcriptomes between porcine oxidative and glycolytic skeletal muscles.

BACKGROUND: MicroRNAs (miRNAs) are a type of non-coding small RNA ~22 nucleotides in length that regulate the expression of protein coding genes at the post-transcriptional level. Glycolytic and oxidative myofibers, the two main types of skeletal muscles, play important roles in metabolic health as well as in meat quality and production in the pig industry. Previous expression profile studies of different skeletal muscle types have focused on these aspects of mRNA and proteins; nonetheless, an explanation of the miRNA transcriptome differences between these two distinct muscles types is long overdue. RESULTS: Herein, we present a comprehensive analysis of miRNA expression profiling between the porcine longissimus doris muscle (LDM) and psoas major muscle (PMM) using a deep sequencing approach. We generated a total of 16.62 M (LDM) and 18.46 M (PMM) counts, which produced 15.22 M and 17.52 M mappable sequences, respectively, and identified 114 conserved miRNAs and 89 novel miRNA*s. Of 668 unique miRNAs, 349 (52.25%) were co-expressed, of which 173 showed significant differences (P < 0.01) between the two muscle types. Muscle-specific miR-1-3p showed high expression levels in both libraries (LDM, 32.01%; PMM, 20.15%), and miRNAs that potentially affect metabolic pathways (such as the miR-133 and -23) showed significant differences between the two libraries, indicating that the two skeletal muscle types shared mainly muscle-specific miRNAs but expressed at distinct levels according to their metabolic needs. In addition, an analysis of the Gene Ontology (GO) terms and KEGG pathway associated with the predicted target genes of the differentially expressed miRNAs revealed that the target protein coding genes of highly expressed miRNAs are mainly involved in skeletal muscle structural development, regeneration, cell cycle progression, and the regulation of cell motility. CONCLUSION: Our study indicates that miRNAs play essential roles in the phenotypic variations observed in different muscle fiber types.

Improving ethanol and xylitol fermentation at elevated temperature through substitution of xylose reductase in Kluyveromyces marxianus.

Thermo-tolerant yeast Kluyveromyces marxianus is able to utilize a wide range of substrates, including xylose; however, the xylose fermentation ability is weak because of the redox imbalance under oxygen-limited conditions. Alleviating the intracellular redox imbalance through engineering the coenzyme specificity of NADPH-preferring xylose reductase (XR) and improving the expression of XR should promote xylose consumption and fermentation. In this study, the native xylose reductase gene (Kmxyl1) of the K. marxianus strain was substituted with XR or its mutant genes from Pichia stipitis (Scheffersomyces stipitis). The ability of the resultant recombinant strains to assimilate xylose to produce xylitol and ethanol at elevated temperature was greatly improved. The strain YZB014 expressing mutant PsXR N272D, which has a higher activity with both NADPH and NADH as the coenzyme, achieved the best results, and produced 3.55 g l(-1) ethanol and 11.32 g l(-1) xylitol-an increase of 12.24- and 2.70-fold in product at 42 °C, respectively. A 3.94-fold increase of xylose consumption was observed compared with the K. marxianus YHJ010 harboring KmXyl1. However, the strain YZB015 expressing a mutant PsXR K21A/N272D, with which co-enzyme preference was completely reversed from NADPH to NADH, failed to ferment due to the low expression. So in order to improve xylose consumption and fermentation in K. marxianus, both higher activity and co-enzyme specificity change are necessary.

Improved xylose fermentation of Kluyveromyces marxianus at elevated temperature through construction of a xylose isomerase pathway.

To improve the xylose fermentation ability of Kluyveromyces marxianus, a xylose assimilation pathway through xylose isomerase was constructed. The genes encoding xylose reductase (KmXyl1) and xylitol dehydrogenase (KmXyl2) were disrupted in K. marxianus YHJ010 and the resultant strain was named YRL002. A codon-optimized xylose isomerase gene from Orpinomyces was transformed into K. marxianus YRL002 and expressed under GAPDH promoter. The transformant was adapted in the SD medium containing 1 % casamino acid with 2 % xylose as sole carbon source. After 32 times of trans-inoculation, a strain named YRL005, which can grow at a specific growth rate of 0.137/h with xylose as carbon source, was obtained. K. marxianus YRL005 could ferment 30.15 g/l of xylose and produce 11.52 g/l ethanol with a yield of 0.38 g/g, production rate of 0.069 g/l/h at 42 °C, and also could ferment 16.60 g/l xylose to produce 5.21 g/l ethanol with a yield of 0.31 g/g, and production rate of 0.054 g/l h at 45 °C. Co-fermentation with 2 % glucose could not improve the amount and yield of ethanol fermented from xylose obviously, but it could improve the production rate. Furthermore, K. marxianus YRL005 can ferment with the corn cob hydrolysate, which contained 20.04 g/l xylose to produce 8.25 g/l ethanol. It is a good platform to construct thermo-tolerant xylose fermentation yeast.

EA-Net: Research on skin lesion segmentation method based on U-Net.

Accurate segmentation of skin lesions is a challenging task because the task is highly influenced by factors such as location, shape and scale. In recent years, Convolutional Neural Networks (CNNs) have achieved advanced performance in automated medical image segmentation. However, existing CNNs have problems such as inability to highlight relevant features and preserve local features, which limit their application in clinical decision-making. This paper proposes a CNN with an added attention mechanism (EA-Net) for more accurate medical image segmentation.EA-Net is based on the U-Net network model framework. Specifically, we added a pixel-level attention module (PA) to the encoder section to preserve the local features of the image during downsampling, making the feature maps input to the decoder more relevant to the ground-truth. At the same time, we added a spatial multi-scale attention module (SA) after the decoding process to increase the spatial weight of the feature maps that are more relevant to the ground-truth, thereby reducing the gap between the output results and the ground-truth. We conducted extensive segmentation experiments on skin lesion images from the ISIC 2017 and ISIC 2018 datasets. The results demonstrate that, when compared to U-Net, our proposed EA-Net achieves an average Dice score improvement of 1.94% and 5.38% for skin lesion tissue segmentation on the ISIC 2017 and ISIC 2018 datasets, respectively. The IoU also increases by 2.69% and 8.31%, and the ASSD decreases by 0.3783 pix and 0.5432 pix, indicating superior segmentation performance. EA-Net can achieve better segmentation results when the original image of skin lesions has an obscure boundary and the segmentation area contains interference factors, which proves that the addition of attention mechanism in the encoder and the application of comprehensive attention mechanism can improve the performance of neural network in the field of skin lesions image segmentation.

Brain tumor feature extraction and edge enhancement algorithm based on U-Net network.

Background: Statistics show that each year more than 100,000 patients pass away from brain tumors. Due to the diverse morphology, hazy boundaries, or unbalanced categories of medical data lesions, segmentation prediction of brain tumors has significant challenges. Purpose: In this thesis, we highlight EAV-UNet, a system designed to accurately detect lesion regions. Optimizing feature extraction, utilizing automatic segmentation techniques to detect anomalous regions, and strengthening the structure. We prioritize the segmentation problem of lesion regions, especially in cases where the margins of the tumor are more hazy. Methods: The VGG-19 network structure is incorporated into the coding stage of the U-Net, resulting in a deeper network structure, and an attention mechanism module is introduced to augment the feature information. Additionally, an edge detection module is added to the encoder to extract edge information in the image, which is then passed to the decoder to aid in reconstructing the original image. Our method uses the VGG-19 in place of the U-Net encoder. To strengthen feature details, we integrate a CBAM (Channel and Spatial Attention Mechanism) module into the decoder to enhance it. To extract vital edge details from the data, we incorporate an edge recognition section into the encoder. Results: All evaluation metrics show major improvements with our recommended EAV-UNet technique, which is based on a thorough analysis of experimental data. Specifically, for low contrast and blurry lesion edge images, the EAV-Unet method consistently produces forecasts that are very similar to the initial images. This technique reduced the Hausdorff distance to 1.82, achieved an F1 score of 96.1%, and attained a precision of 93.2% on Dataset 1. It obtained an F1 score of 76.8%, a Precision of 85.3%, and a Hausdorff distance reduction to 1.31 on Dataset 2. Dataset 3 displayed a Hausdorff distance cut in 2.30, an F1 score of 86.9%, and Precision of 95.3%. Conclusions: We conducted extensive segmentation experiments using various datasets related to brain tumors. We refined the network architecture by employing smaller convolutional kernels in our strategy. To further improve segmentation accuracy, we integrated attention modules and an edge enhancement module to reinforce edge information and boost attention scores.