Improving feature selection performance for classification of gene expression data using Harris Hawks optimizer with variable neighborhood learning.

Gene expression profiling has played a significant role in the identification and classification of tumor molecules. In gene expression data, only a few feature genes are closely related to tumors. It is a challenging task to select highly discriminative feature genes, and existing methods fail to deal with this problem efficiently. This article proposes a novel metaheuristic approach for gene feature extraction, called variable neighborhood learning Harris Hawks optimizer (VNLHHO). First, the F-score is used for a primary selection of the genes in gene expression data to narrow down the selection range of the feature genes. Subsequently, a variable neighborhood learning strategy is constructed to balance the global exploration and local exploitation of the Harris Hawks optimization. Finally, mutation operations are employed to increase the diversity of the population, so as to prevent the algorithm from falling into a local optimum. In addition, a novel activation function is used to convert the continuous solution of the VNLHHO into binary values, and a naive Bayesian classifier is utilized as a fitness function to select feature genes that can help classify biological tissues of binary and multi-class cancers. An experiment is conducted on gene expression profile data of eight types of tumors. The results show that the classification accuracy of the VNLHHO is greater than 96.128% for tumors in the colon, nervous system and lungs and 100% for the rest. We compare seven other algorithms and demonstrate the superiority of the VNLHHO in terms of the classification accuracy, fitness value and AUC value in feature selection for gene expression data.

Impaired retinal microcirculation in patients with non-obstructive coronary artery disease.

PURPOSE: To quantitatively investigate alterations of retinal microcirculation in patients with non-obstructive coronary artery disease (NOCAD) using optical coherence tomography angiography (OCTA), and to identify the ability of retinal microcirculation parameters in differentiating coronary artery disease (CAD) subtypes. METHODS: All participants with angina pectoris underwent coronary computed tomography angiography. Patients with lumen diameter reduction of 20-50 % in all major coronary arteries were defined as NOCAD, while patients with at least one major coronary artery lumen diameter reduction ≥ 50 % were recruited as obstructive coronary artery disease (OCAD). Participants without a history of ophthalmic or systemic vascular disease were recruited as healthy controls. Retinal neural-vasculature was measured quantitatively by OCTA, including peripapillary retinal nerve fiber layer (RNFL) thickness and vessel density (VD) of the optic disc, superficial vessel plexus (SVP), deep vessel plexus (DVP), and foveal density (FD 300). p < 0.017 is considered significant in multiple comparisons. RESULTS: A total of 185 participants (65 NOCAD, 62 OCAD, and 58 controls) were enrolled. Except for the DVP fovea (p = 0.069), significantly reduced VD in all other regions of SVP and DVP was detected in both the NOCAD and OCAD groups compared to control group (all p < 0.017), while a more significant decrease was found in OCAD compared to NOCAD. Multivariate regression analysis showed that lower VD in superior hemi part of whole SVP (OR: 0.582, 95 % CI: 0.451-0.752) was an independent risk factor for NOCAD compared to controls, while lower VD in the whole SVP (OR: 0.550, 95 % CI: 0.421-0.719) was an independent risk factor for OCAD compared to NOCAD. Using the integration of retinal microvascular parameters, the area under the receiver operating characteristic curve (AUC) for NOCAD versus control and OCAD versus NOCAD were 0.840 and 0.830, respectively. CONCLUSION: Significant retinal microcirculation impairment, while milder than that in OCAD was observed in NOCAD patients, indicating retinal microvasculature assessment might provide a new systemic microcirculation observation window for NOCAD. Furthermore, retinal microvasculature may serve as a new indicator to assess the severity of CAD with good performance of retinal microvascular parameters in identifying different CAD subtypes.

Climatic seasonality challenges the stability of microbial-driven deep soil carbon accumulation across China.

Microbial residues contribute to the long-term stabilization of carbon in the entire soil profile, helping to regulate the climate of the planet; however, how sensitive these residues are to climatic seasonality remains virtually unknown, especially for deep soils across environmental gradients. Here, we investigated the changes of microbial residues along soil profiles (0-100 cm) from 44 typical ecosystems with a wide range of climates (~3100 km transects across China). Our results showed that microbial residues account for a larger portion of soil carbon in deeper (60-100 cm) vs. shallower (0-30 and 30-60 cm) soils. Moreover, we find that climate especially challenges the accumulation of microbial residues in deep soils, while soil properties and climate share their roles in controlling the residue accumulation in surface soils. Climatic seasonality, including positive correlations with summer precipitation and maximum monthly precipitation, as well as negative correlations with temperature annual range, are important factors explaining microbial residue accumulation in deep soils across China. In particular, summer precipitation is the key regulator of microbial-driven carbon stability in deep soils, which has 37.2% of relative independent effects on deep-soil microbial residue accumulation. Our work provides novel insights into the importance of climatic seasonality in driving the stabilization of microbial residues in deep soils, challenging the idea that deep soils as long-term carbon reservoirs can buffer climate change.

Metagenomics revealing molecular profiles of microbial community structure and metabolic capacity in Bamucuo lake, Tibet.

Microorganisms play critical ecological roles in the global biogeochemical cycles. However, extensive information on the microbial communities in Qinghai-Tibet Plateau (QTP), which is the highest plateau in the world, is still lacking, particularly in high elevation locations above 4500 m. Here, we performed a survey of th e soil and water microbial communities in Bamucuo Lake, Tibet, by using shotgun metagenomic methods. In the soil and water samples, we reconstructed 75 almost complete metagenomic assembly genomes, and 74 of the metagenomic assembly genomes from the water sample represented novel species. Proteobacteria and Actinobacteria were found to be the dominant bacterial phyla, while Euryarchaeota was the dominant archaeal phylum. The largest virus, Pandoravirus salinus, was found in the soil microbial community. We concluded that the microorganisms in Bamucuo Lake are most likely to fix carbon mainly through the 3-hydroxypropionic bi-cycle pathway. This study, for the first time, characterized the microbial community composition and metabolic capacity in QTP high-elevation locations with 4555 m, confirming that QTP is a vast and valuable resource pool, in which many microorganisms can be used to develop new bioactive substances and new antibiotics to which pathogenic microorganisms have not yet developed resistance.

The effects of intrinsic water-use efficiency and climate on wood anatomy.

Climate warming may induce growth decline in warm-temperate areas subjected to seasonal soil moisture deficit, whereas increasing atmospheric CO2 concentration (Ca) is expected to enhance tree growth. An accurate understanding of tree growth and physiological processes responding to climate warming and increasing Ca is critical. Here, we analyzed tree-ring stable carbon isotope and wood anatomical traits of Pinus tabuliformis from Qinling Mountains in China to understand how lumen diameter (LD) determining potential hydraulic conductivity and cell-wall thickness (CWT) determining carbon storage responded to climate and Ca. The effects of climate and Ca on intrinsic water-use efficiency (iWUE) were isolated, and iWUE values due to only-climate (iWUEClim) and only-CO2 effects (iWUECO2) were obtained. During a low-iWUE period, the influences of climate on earlywood (EW) LD and latewood (LW) CWT prevailed. During a high-iWUE period, CO2 fertilization promoted cell enlargement and carbon storage but this was counteracted by a negative influence of climate warming. The limiting direct effects of iWUEClim and indirect effects of climate on EW LD were greater than on LW CWT. P. tabuliformis in temperate forests will face a decline of growth and carbon fixation, but will produce embolism-resistant tracheids with narrow lumen responding to future hotter droughts.

Molecular evolutionary characteristics of SARS-CoV-2 emerging in the United States.

SARS-CoV-2 is a newly discovered beta coronavirus at the end of 2019, which is highly pathogenic and poses a serious threat to human health. In this paper, 1875 SARS-CoV-2 whole genome sequences and the sequence coding spike protein (S gene) sampled from the United States were used for bioinformatics analysis to study the molecular evolutionary characteristics of its genome and spike protein. The MCMC method was used to calculate the evolution rate of the whole genome sequence and the nucleotide mutation rate of the S gene. The results showed that the nucleotide mutation rate of the whole genome was 6.677 × 10-4 substitution per site per year, and the nucleotide mutation rate of the S gene was 8.066 × 10-4 substitution per site per year, which was at a medium level compared with other RNA viruses. Our findings confirmed the scientific hypothesis that the rate of evolution of the virus gradually decreases over time. We also found 13 statistically significant positive selection sites in the SARS-CoV-2 genome. In addition, the results showed that there were 101 nonsynonymous mutation sites in the amino acid sequence of S protein, including seven putative harmful mutation sites. This paper has preliminarily clarified the evolutionary characteristics of SARS-CoV-2 in the United States, providing a scientific basis for future surveillance and prevention of virus variants.

Local temperature increases reduce soil microbial residues and carbon stocks.

Warming is known to reduce soil carbon (C) stocks by promoting microbial respiration, which is associated with the decomposition of microbial residue carbon (MRC). However, the relative contribution of MRC to soil organic carbon (SOC) across temperature gradients is poorly understood. Here, we investigated the contribution of MRC to SOC along two independent elevation gradients of our model system (i.e., the Tibetan Plateau and Shennongjia Mountain in China). Our results showed that local temperature increases were negatively correlated with MRC and SOC. Further analyses revealed that rising temperature reduced SOC via decreasing MRC, which helps to explain future reductions in SOC under climate warming. Our findings demonstrate that climate warming has the potential to reduce C sequestration by increasing the decomposition of MRC, exacerbating the positive feedback between rising temperature and CO2 efflux. Our study also considered the influence of multiple environmental factors such as soil pH and moisture, which were more important in controlling SOC than microbial traits such as microbial life-style strategies and metabolic efficiency. Together, our work suggests an important mechanism underlying long-term soil C sequestration, which has important implications for the microbial-mediated C process in the face of global climate change.

Global diversity and ecological drivers of lichenised soil fungi.

Lichens play crucial roles in sustaining the functioning of terrestrial ecosystems; however, the diversity and ecological factors associated with lichenised soil fungi remain poorly understood. To address this knowledge gap, we used a global field survey including information on fungal sequences of topsoils from 235 terrestrial ecosystems. We identified 880 lichenised fungal phylotypes across nine biomes ranging from deserts to tropical forests. The diversity and proportion of lichenised soil fungi peaked in shrublands and dry grasslands. Aridity index, plant cover and soil pH were the most important factors associated with the distribution of lichenised soil fungi. Furthermore, we identified Endocarpon, Verrucaria and Rinodina as some of the most dominant lichenised genera across the globe, and they had similar environmental preferences to the lichenised fungal community. In addition, precipitation seasonality and mean diurnal temperature range were also important in predicting the proportion of these dominant genera. Using this information, we were able to create the first global maps of the richness and the proportion of dominant genera of lichenised fungi. This work provides new insight into the global distribution and ecological preferences of lichenised soil fungi, and supports their dominance in drylands across the globe.

DETECTION OF MORPHOLOGIC PATTERNS OF DIABETIC MACULAR EDEMA USING A DEEP LEARNING APPROACH BASED ON OPTICAL COHERENCE TOMOGRAPHY IMAGES.

PURPOSE: To develop a deep learning (DL) model to detect morphologic patterns of diabetic macular edema (DME) based on optical coherence tomography (OCT) images. METHODS: In the training set, 12,365 OCT images were extracted from a public data set and an ophthalmic center. A total of 656 OCT images were extracted from another ophthalmic center for external validation. The presence or absence of three OCT patterns of DME, including diffused retinal thickening, cystoid macular edema, and serous retinal detachment, was labeled with 1 or 0, respectively. A DL model was trained to detect three OCT patterns of DME. The occlusion test was applied for the visualization of the DL model. RESULTS: Applying 5-fold cross-validation method in internal validation, the area under the receiver operating characteristic curve for the detection of three OCT patterns (i.e., diffused retinal thickening, cystoid macular edema, and serous retinal detachment) was 0.971, 0.974, and 0.994, respectively, with an accuracy of 93.0%, 95.1%, and 98.8%, respectively, a sensitivity of 93.5%, 94.5%, and 96.7%, respectively, and a specificity of 92.3%, 95.6%, and 99.3%, respectively. In external validation, the area under the receiver operating characteristic curve was 0.970, 0.997, and 0.997, respectively, with an accuracy of 90.2%, 95.4%, and 95.9%, respectively, a sensitivity of 80.1%, 93.4%, and 94.9%, respectively, and a specificity of 97.6%, 97.2%, and 96.5%, respectively. The occlusion test showed that the DL model could successfully identify the pathologic regions most critical for detection. CONCLUSION: Our DL model demonstrated high accuracy and transparency in the detection of OCT patterns of DME. These results emphasized the potential of artificial intelligence in assisting clinical decision-making processes in patients with DME.

Feasibility study of early prediction of postoperative MRI findings for knee stability after anterior cruciate ligament reconstruction.

BACKGROUND: At present, the most effective and mature treatment after ACL injury and tear is ACL reconstruction, but the rehabilitation process after ACL reconstruction that is very long, so it is very important to find early MRI positive findings of knee instability. METHODS: We retrospectively collected the clinical and imaging data of 70 patients who underwent ACL reconstruction from January 2016 to December 2019; Based on clinical criteria, the patients were divided into a stable group (n = 57) and an unstable group (n = 13); We measured the MRI imaging evaluation indexes, including the position of the bone tunnel, graft status, and the anatomical factors; Statistical methods were used to compare the differences of imaging evaluation indexes between the two groups; The prediction equation was constructed and ROC curve was used to compare the prediction efficiency of independent prediction factors and prediction equation. RESULTS: There were significant differences in the abnormal position of tibial tunnel entrance, percentage of the position of tibial tunnel entrance, position of tibial tunnel exit, lateral tibial posterior slope (LTPS), width of intercondylar notch between stable knee joint group and unstable knee joint group after ACL reconstruction (P < 0.05); The position of tibial tunnel exits and the lateral tibial posterior slope (LTPS) and the sagittal obliquity of the graft were independent predictors among surgical factors and self-anatomical factors (P < 0.05); The prediction equation of postoperative knee stability was established: Logit(P) = -1.067-0.231*position of tibial tunnel exit + 0.509*lateral tibial posterior slope (LTPS)-2.105*sagittal obliquity of the graft; The prediction equation predicted that the AUC of knee instability was 0.915, the sensitivity was 84.6%, and the specificity was 91.2%. CONCLUSIONS: We found that abnormalities of the position of the exit of the bone tunnel, lateral tibial posterior slope (LTPS) and sagittal obliquity of the graft were the early MRI positive findings of knee instability after ACL reconstruction. It is helpful for clinicians to predict the stability of knee joint after ACL reconstruction.

Adding vitamin D3 to the dipeptidyl peptidase-4 inhibitor saxagliptin has the potential to protect ß-cell function in LADA patients: A 1-year pilot study.

AIMS: This trial was conducted to explore the protective effect on ß-cell function of adding vitamin D3 to DPP-4 inhibitors to treat patients with latent autoimmune diabetes in adults (LADA). METHODS: 60 LADA patients were randomized to group A (n = 21) - conventional therapy with metformin (1-1.7 g/day) and/or insulin treatment; group B (n = 20) - saxagliptin (5 mg/day) plus conventional therapy; and group C (n = 19) - vitamin D3 (2000 IU/day) plus saxagliptin and conventional therapy for 12 months. Fasting and 2-hour postprandial blood samples were collected to measure blood glucose, glycosylated hemoglobin and C-peptide levels at baseline and after 3, 6 and 12 months of treatment. RESULTS: During the 12 months of follow-up, the levels of fasting C-peptide (FCP), 2-hour postprandial C-peptide (PCP) and the C-peptide index (CPI, serum C-peptide-to-plasma glucose level ratio) were maintained in group C. In contrast to those in group A and group B, FCP levels decreased significantly in group B, and CPI levels declined significantly in group A during the 1-year treatment (P < .05). Additionally, the levels of GADA titers in group C significantly decreased compared with those at baseline (P < .05), but no significant differences in GADA titers levels were detected in group A and group B. No significant differences were found among the three groups in the levels of FCP, PCP, the CPI or GADA titers. CONCLUSIONS: The data suggested that adding 2000 IU/day vitamin D3 to saxagliptin might preserve ß-cell function in patients with LADA.

Retinal microvasculature impairment in patients with congenital heart disease investigated by optical coherence tomography angiography.

IMPORTANCE: A high prevalence of retinal abnormalities have been reported in congenital heart disease (CHD), but quantitative analysis of retinal vasculature is scarce. Optical coherence tomography angiography (OCTA) is a noninvasive method to quantitatively assess the retinal microvasculature. BACKGROUND: To investigate the retinal microvasculature changes in CHD patients by using OCTA. DESIGN: Cross-sectional study. PARTICIPANTS: A total of 158 participants including 57 cyanotic CHD (CCHD) patients, 60 acyanotic CHD (ACHD) patients and 41 control subjects were included. METHODS: All participants underwent a comprehensive ophthalmologic examination, including refraction measurement, intraocular pressure measurement and OCTA. MAIN OUTCOME MEASURES: Vessel density (VD) was measured within the radial peripapillary capillary (RPC), superficial capillary plexus (SCP) and deep capillary plexus (DCP) of the macula. RESULTS: CCHD patients had significantly lower VD in the RPC, SCP and DCP (all P < .01) compared to control subjects, and significantly lower VD in the RPC and DCP (both P < .05) compared to ACHD patients. Besides, among the CHD group, VD in the RPC was positively correlated with oxygen saturation (whole image, ρ = 0.45; peripapillary, ρ = 0.48) and negatively correlated with haematocrit (whole image, ρ = 0.55; peripapillary, ρ = 0.55) (all P < .001). CONCLUSIONS AND RELEVANCE: Retinal VD might be a surrogate to reflect the effect of chronic systemic hypoxemia in CHD patients. OCTA could be a convenient and noninvasive tool to evaluate the retinal structure and function in CHD patients.

Climate signals in tree-ring δ18 O and δ13 C from southeastern Tibet: insights from observations and forward modelling of intra- to interdecadal variability.

Stable isotopes in tree rings are increasingly used as proxies for climatic and ecophysiological changes. However, uncertainties remain about the strength and consistency of their response to environmental variation at different temporal (i.e. seasonal to inter-decadal) scales. We developed 5 yr of intra-seasonal and 62 yr of early- and late-wood δ13 C and δ18 O series of Smith fir (Abies georgei var. smithii) on the southeastern Tibetan Plateau, and used a process-based forward model to examine the relative importance of environmental and physiological controls on the isotopic data. In this temperate high-altitude region, the response, both δ18 O and δ13 C, is primarily to variations in relative humidity, but by different processes. In δ18 O, the response is via source water δ18 O but also arises from leaf water 18 O enrichment. In δ13 C, the response is via changes in stomatal conductance but is modified by carry-over effects from prior periods. We conclude that tree-ring δ18 O may be a more robust climate proxy than δ13 C, and δ13 C may be more suited to studies of site-related physiological responses to the local environment.

[A SAS marco program for batch processing of univariate Cox regression analysis for great database].

OBJECTIVE: To realize batch processing of univariate Cox regression analysis for great database by SAS marco program. METHODS: We wrote a SAS macro program, which can filter, integrate, and export P values to Excel by SAS9.2. The program was used for screening survival correlated RNA molecules of ovarian cancer. RESULTS: A SAS marco program could finish the batch processing of univariate Cox regression analysis, the selection and export of the results. CONCLUSION: The SAS macro program has potential applications in reducing the workload of statistical analysis and providing a basis for batch processing of univariate Cox regression analysis.

[Comprehensive evaluation of sample data in medical research].

Comprehensive evaluation methods are generally used to assess the population data. When we need to estimate the sample data in special situations, the impacts brought by the sampling error should be considered. Due to lack of the accurate measurement for the sensitivity and stability in the comprehensive evaluation methods, sampling errors usually cannot be estimated in the sampling research. Monte Carlo simulation was used in this article to solve the probability of the ordering results, and the matlab programs were presented. Based on the simulated results, we change the conventional "absolute conclusion" of comprehensive evaluation methods to "probability results" for the sample data, and put forward a new sorting and ranking method for the results of comprehensive evaluation.

[DNA detection and sequence analysis of spotted fever group Rickettsiae in rodents from Heilongjiang forest region].

OBJECTIVE: To investigate the infection in spotted fever group Rickettsiae (SFGR) in wild rodents from Heilongjiang, China. METHODS: Polymerase chain reaction (PCR) was used to detect the OmpA gene of SFGR in rodents collected in Heilongjiang. The PCR products amplified from rodent specimens were sequenced and compared with the corresponding part of the sequences deposited in the GenBank. Phylogenetic trees were constructed with Mega 5.0 software. RESULTS: A total of 514 rodents were collected from Heilongjiang during 2009-2011 and 11 species were included. The infection rate of SFGR in the rodents was 9.3% (95% CI: 7.1%-12.2%). Statistical analysis showed a significant difference in different areas of Heilongjiang (P=0.023). The highest prevalence was observed in Mudanjing area (12.42%). There were significant differences in different species of rodents (P=0.002). The infection rate of SFGR determined in Clethrionomys rufocanus was the highest (22.1%). Sequence analysis revealed SFGR belonged to R.heilongjiangensis and a new unknown rickettsia genotype. CONCLUSION: R.heilongjiangensis has been presented in rodents in Heilongjiang, and a new SFGR genotype different from other rickettsiae genotypes may exist in this area.

A new hybrid algorithm for three-stage gene selection based on whale optimization.

In biomedical data mining, the gene dimension is often much larger than the sample size. To solve this problem, we need to use a feature selection algorithm to select feature gene subsets with a strong correlation with phenotype to ensure the accuracy of subsequent analysis. This paper presents a new three-stage hybrid feature gene selection method, that combines a variance filter, extremely randomized tree, and whale optimization algorithm. First, a variance filter is used to reduce the dimension of the feature gene space, and an extremely randomized tree is used to further reduce the feature gene set. Finally, the whale optimization algorithm is used to select the optimal feature gene subset. We evaluate the proposed method with three different classifiers in seven published gene expression profile datasets and compare it with other advanced feature selection algorithms. The results show that the proposed method has significant advantages in a variety of evaluation indicators.

A novel hybrid algorithm based on Harris Hawks for tumor feature gene selection.

Background: Gene expression data are often used to classify cancer genes. In such high-dimensional datasets, however, only a few feature genes are closely related to tumors. Therefore, it is important to accurately select a subset of feature genes with high contributions to cancer classification. Methods: In this article, a new three-stage hybrid gene selection method is proposed that combines a variance filter, extremely randomized tree and Harris Hawks (VEH). In the first stage, we evaluated each gene in the dataset through the variance filter and selected the feature genes that meet the variance threshold. In the second stage, we use extremely randomized tree to further eliminate irrelevant genes. Finally, we used the Harris Hawks algorithm to select the gene subset from the previous two stages to obtain the optimal feature gene subset. Results: We evaluated the proposed method using three different classifiers on eight published microarray gene expression datasets. The results showed a 100% classification accuracy for VEH in gastric cancer, acute lymphoblastic leukemia and ovarian cancer, and an average classification accuracy of 95.33% across a variety of other cancers. Compared with other advanced feature selection algorithms, VEH has obvious advantages when measured by many evaluation criteria.

Functional magnetic resonance imaging reveals dysfunction of the paraspinal muscles in patients with chronic low back pain: a cross-sectional study.

Background: Patients with chronic low back pain (CLBP) undergo structural changes of the paraspinal muscles; however, it is unclear if functional changes also occur. This study aimed to examine the metabolic and perfusion function changes in the paraspinal muscles of patients with CLBP as indirectly reflected by blood oxygen level-dependent (BOLD) imaging and T2 mapping. Methods: All participants were consecutively enrolled at our local hospital from December 2019 to November 2020. Patients were diagnosed with CLBP in the outpatient clinic, and asymptomatic participants were considered to be those with no CLBP or other diseases. This study was not registered on a clinical trial platform. Participants underwent BOLD imaging and T2 mapping scans at the L4-S1 disc level. The effective transverse relaxation rate (R2* values) and transverse relaxation time (T2 values) of the paraspinal muscles were measured on the central plane of the L4/5 and L5/S1 intervertebral discs. Finally, the independent samples t-test was used to assess the differences in R2* and T2 values between the 2 groups, while Pearson correlation analysis was used to determine their correlation with age. Results: A total of 60 patients with CLBP and 20 asymptomatic participants were enrolled. The paraspinal muscles of the CLBP group had higher total R2* values [46.7±2.9 vs. 44.0±2.9 s-1; 95% confidence interval (CI): 1.2-4.2; P=0.001] and lower total T2 values (45.4±4.2 vs. 47.1±3.7 ms; 95% CI: -3.8 to 0.4; P=0.109) than did the asymptomatic participants. For the different muscles, R2* values for the erector spinae (ES) (L4/5: 45.5±2.6 vs. 43.0±3.0 s-1, 95% CI: 1.1-4.0, P=0.001; L5/S1: 48.5±4.9 vs. 45.9±4.2 s-1; 95% CI: 0.2-5.1; P=0.035) and the R2* values of the multifidus (MF) muscles (L4/5: 46.4±2.9 vs. 43.7±3.5 s-1, 95% CI: 1.1-4.3, P=0.001; L5/S1: 46.3±3.5 vs. 42.5±2.8 s-1, 95% CI: 2.1-5.5, P<0.001) of the CLBP group at both spinal levels were higher than those of the asymptomatic participants. In the patients with CLBP, the R2* values at the L4/5 (45.9±2.1 s-1) were lower than those at the L5/S1 (47.4±3.6 s-1; 95% CI: -2.6 to -0.4; P=0.007). The R2* values were positively correlated with age in both groups (CLBP group: r=0.501, 95% CI: 0.271-0.694, P<0.001; asymptomatic group: r=0.499, 95% CI: -0.047 to 0.771; P=0.025). Conclusions: The R2* values were higher in the paraspinal muscles of patients with CLPB and may suggest metabolic and perfusion dysfunction of the paraspinal muscles in these patients.

Enhancement patterns of potassium on nitrogen transport and functional genes in cotton vary with nitrogen levels.

The application of potassium (K) in conjunction with nitrogen (N) has been shown to enhance N use efficiency. However, there is still a need for further understanding of the optimal ratios and molecular regulatory mechanisms, particularly in soil-cotton systems. Here, a field trial was conducted, involving varying rates of N and K, alongside pot and hydroponic experiments. The objective was to assess the impact of N-K interaction on the absorption, transport and distribution of N in cotton. The results showed that K supply at 90 and 240 kg ha-1 had a beneficial impact on N uptake and distribution to both seed and lint, resulting in the highest N use efficiency ranging from 22% to 62% and yield improvements from 20% to 123%. The increase in stem and root diameters, rather than the quantify of xylem vessels and phloem sieve tubes, facilitated the uptake and transport of N due to the provision of K. At the molecular level, K supply upregulated the expression levels of genes encoding GhNRT2.1 transporter and GhSLAH3 channel in cotton roots to promote N uptake and GhNRT1.5/NPF7.3 genes to transport N to shoot under low-N conditions. However, under high-N conditions, K supply induced anion channel genes (GhSLAH4) of roots to promote N uptake and genes encoding GhNRT1.5/NPF7.3 and GhNRT1.8/NPF7.2 transporters to facilitate NO3- unloading from xylem to mesophyll cell in high-N plants. Furthermore, K supply resulted in the upregulation of gene expression for GhGS2 in leaves, while simultaneously downregulating the expression of GhNADH-GOGAT, GhGDH1 and GhGDH3 genes in high-N roots. The enzyme activities of nitrite reductase and glutamine synthetase increased and glutamate dehydrogenase decreased, but the concentration of NO3- and soluble protein exhibited a significant increase and free amino acid decreased in the shoots subsequent to K supply.