BlockPolish: accurate polishing of long-read assembly via block divide-and-conquer.

Long-read sequencing technology enables significant progress in de novo genome assembly. However, the high error rate and the wide error distribution of raw reads result in a large number of errors in the assembly. Polishing is a procedure to fix errors in the draft assembly and improve the reliability of genomic analysis. However, existing methods treat all the regions of the assembly equally while there are fundamental differences between the error distributions of these regions. How to achieve very high accuracy in genome assembly is still a challenging problem. Motivated by the uneven errors in different regions of the assembly, we propose a novel polishing workflow named BlockPolish. In this method, we divide contigs into blocks with low complexity and high complexity according to statistics of aligned nucleotide bases. Multiple sequence alignment is applied to realign raw reads in complex blocks and optimize the alignment result. Due to the different distributions of error rates in trivial and complex blocks, two multitask bidirectional Long short-term memory (LSTM) networks are proposed to predict the consensus sequences. In the whole-genome assemblies of NA12878 assembled by Wtdbg2 and Flye using Nanopore data, BlockPolish has a higher polishing accuracy than other state-of-the-arts including Racon, Medaka and MarginPolish & HELEN. In all assemblies, errors are predominantly indels and BlockPolish has a good performance in correcting them. In addition to the Nanopore assemblies, we further demonstrate that BlockPolish can also reduce the errors in the PacBio assemblies. The source code of BlockPolish is freely available on Github (https://github.com/huangnengCSU/BlockPolish).

compleasm: a faster and more accurate reimplementation of BUSCO.

MOTIVATION: Evaluating the gene completeness is critical to measuring the quality of a genome assembly. An incomplete assembly can lead to errors in gene predictions, annotation, and other downstream analyses. Benchmarking Universal Single-Copy Orthologs (BUSCO) is a widely used tool for assessing the completeness of genome assembly by testing the presence of a set of single-copy orthologs conserved across a wide range of taxa. However, BUSCO is slow particularly for large genome assemblies. It is cumbersome to apply BUSCO to a large number of assemblies. RESULTS: Here, we present compleasm, an efficient tool for assessing the completeness of genome assemblies. Compleasm utilizes the miniprot protein-to-genome aligner and the conserved orthologous genes from BUSCO. It is 14 times faster than BUSCO for human assemblies and reports a more accurate completeness of 99.6% than BUSCO's 95.7%, which is in close agreement with the annotation completeness of 99.5% for T2T-CHM13. AVAILABILITY AND IMPLEMENTATION: https://github.com/huangnengCSU/compleasm.

NanoSNP: a progressive and haplotype-aware SNP caller on low-coverage nanopore sequencing data.

MOTIVATION: Oxford Nanopore sequencing has great potential and advantages in population-scale studies. Due to the cost of sequencing, the depth of whole-genome sequencing for per individual sample must be small. However, the existing single nucleotide polymorphism (SNP) callers are aimed at high-coverage Nanopore sequencing reads. Detecting the SNP variants on low-coverage Nanopore sequencing data is still a challenging problem. RESULTS: We developed a novel deep learning-based SNP calling method, NanoSNP, to identify the SNP sites (excluding short indels) based on low-coverage Nanopore sequencing reads. In this method, we design a multi-step, multi-scale and haplotype-aware SNP detection pipeline. First, the pileup model in NanoSNP utilizes the naive pileup feature to predict a subset of SNP sites with a Bi-long short-term memory (LSTM) network. These SNP sites are phased and used to divide the low-coverage Nanopore reads into different haplotypes. Finally, the long-range haplotype feature and short-range pileup feature are extracted from each haplotype. The haplotype model combines two features and predicts the genotype for the candidate site using a Bi-LSTM network. To evaluate the performance of NanoSNP, we compared NanoSNP with Clair, Clair3, Pepper-DeepVariant and NanoCaller on the low-coverage (∼16×) Nanopore sequencing reads. We also performed cross-genome testing on six human genomes HG002-HG007, respectively. Comprehensive experiments demonstrate that NanoSNP outperforms Clair, Pepper-DeepVariant and NanoCaller in identifying SNPs on low-coverage Nanopore sequencing data, including the difficult-to-map regions and major histocompatibility complex regions in the human genome. NanoSNP is comparable to Clair3 when the coverage exceeds 16×. AVAILABILITY AND IMPLEMENTATION: https://github.com/huangnengCSU/NanoSNP.git. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The efficacy and safety of autologous epidermal cell suspensions for re-epithelialization of skin lesions: A systematic review and meta-analysis of randomized trials.

BACKGROUND: Successful usage of autologous skin cell suspension (ASCS) has been demonstrated in some clinical trials. However, its efficacy and safety have not been verified. This latest systematic review and meta-analysis aim to examine the effects of autologous epidermal cell suspensions in re-epithelialization of skin lesions. METHODS: Relevant articles were retrieved from PubMed, Embase, Cochrane Database, Web of Science, International Clinical Trials Registry Platform, China National Knowledge Infrastructureris, VIP Database for Chinese Technical Periodicals and Wanfang database. The primary output measure was the healing time, and the secondary outputs were effective rate, size of donor site for treatment, size of study treatment area, operation time, pain scores, repigmentation, complications, scar scale scores and satisfaction scores. Data were pooled and expressed as relative risk (RR), mean difference (MD) and standardized mean difference (SMD) with a 95% confidence interval (CI). RESULTS: Thirty-one studies were included in this systematic review and meta-analysis, with 914 patients who received autologous epidermal cell suspensions (treatment group) and 883 patients who received standard care or placebo (control group). The pooled data from all included studies demonstrated that the treatment group has significantly reduced healing time (SMD = -0.86; 95% CI: -1.59-0.14; p = 0.02, I2 = 95%), size of donar site for treatment (MD = -115.41; 95% CI: -128.74-102.09; p<0.001, I2 = 89%), operation time (MD = 25.35; 95% CI: 23.42-27.29; p<0.001, I2 = 100%), pain scores (SMD = -1.88; 95% CI: -2.86-0.90; p = 0.0002, I2 = 89%) and complications (RR = 0.59; 95% CI: 0.36-0.96; p = 0.03, I2 = 66%), as well as significantly increased effective rate (RR = 1.20; 95% CI: 1.01-1.42; p = 0.04, I2 = 77%). There were no significant differences in the size of study treatment area, repigmentation, scar scale scores and satisfaction scores between the two groups. CONCLUSION: Our meta-analysis showed that autologous epidermal cell suspensions is beneficial for re-epithelialization of skin lesions as they significantly reduce the healing time, size of donar site for treatment, operation time, pain scores and complications, as well as increased effective rate. However, this intervention has minimal impact on size of treatment area, repigmentation, scar scale scores and satisfaction scores.

Effects of Virtual Reality on Analgesia in Wound Care and Physical Therapy for Burn Patients: A Systematic Review and Meta-analysis.

OBJECTIVES: This systematic review and meta-analysis aimed to determine the effectiveness of virtual reality (VR) in alleviating pain and improving the experience of burn patients during wound care and physical therapy. DESIGN: A systematic review and meta-analysis. DATA SOURCES: PubMed, Embase, the Cochrane Database, and the Web of Science. REVIEW/ANALYSIS METHODS: We searched four electronic databases for randomized controlled trials (RCTs) published from the earliest available date up to March 1, 2022. The primary outcome was worst pain intensity, while secondary outcomes encompassed pain unpleasantness intensity, time spent thinking about pain, and fun experience intensity. Risk of bias was evaluated using the Cochrane Collaboration's tool. RESULTS: This study included 21 trials. The combined data revealed that the VR group experienced a significant reduction in worst pain intensity, pain unpleasantness intensity, and time spent thinking about pain compared to the control group. Moreover, VR treatment was associated with a significant increase in the fun experience intensity. IMPLICATIONS FOR NURSING: Virtual reality has the potential value of auxiliary analgesia in burn care, and exploring a more perfect scheme of VR-assisted analgesia is worthwhile. CONCLUSIONS: The results of this meta-analysis indicate that VR can effectively reduce worst pain intensity, pain unpleasantness intensity, and time spent thinking about pain during wound care and physical therapy for burn patients. Additionally, it enhances fun experience intensity of the treatment period. Therefore, VR shows promise as a valuable complementary pain management intervention for burn patients.

Fec: a fast error correction method based on two-rounds overlapping and caching.

The third-generation sequencing technology has advanced genome analysis with long-read length, but the reads need error correction due to the high error rate. Error correction is a time-consuming process especially when the sequencing coverage is high. Generally, for a pair of overlapping reads A and B, the existing error correction methods perform a base-level alignment from B to A when correcting the read A. And another base-level alignment from A to B is performed when correcting the read B. However, based on our observation, the base-level alignment information can be reused. In this article, we present a fast error correction tool Fec, using two-rounds overlapping and caching. Fec can be used independently or as an error correction step in an assembly pipeline. In the first round, Fec uses a large window size (20) to quickly find enough overlaps to correct most of the reads. In the second round, a small window size (5) is used to find more overlaps for the reads with insufficient overlaps in the first round. When performing base-level alignment, Fec searches the cache first. If the alignment exists in the cache, Fec takes this alignment out and deduces the second alignment from it. Otherwise, Fec performs base-level alignment and stores the alignment in the cache. We test Fec on nine datasets, and the results show that Fec has 1.24-38.56 times speed-up compared to MECAT, CANU and MINICNS on five PacBio datasets and 1.16-27.8 times speed-up compared to NECAT and CANU on four nanopore datasets. AVAILABILITY AND IMPLEMENTATION: Fec is available at https://github.com/zhangjuncsu/Fec. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MultiNanopolish: refined grouping method for reducing redundant calculations in Nanopolish.

MOTIVATION: Compared with the second-generation sequencing technologies, the third-generation sequencing technologies allows us to obtain longer reads (average ∼10 kbps, maximum 900 kbps), but brings a higher error rate (∼15% error rate). Nanopolish is a variant and methylation detection tool based on hidden Markov model, which uses Oxford Nanopore sequencing data for signal-level analysis. Nanopolish can greatly improve the accuracy of assembly, whereas it is limited by long running time since most executive parts of Nanopolish is a serial and computationally expensive process. RESULTS: In this paper, we present an effective polishing tool, Multithreading Nanopolish (MultiNanopolish), which decomposes the whole process of iterative calculation in Nanopolish into small independent calculation tasks, making it possible to run this process in the parallel mode. Experimental results show that MultiNanopolish reduces running time by 50% with read-uncorrected assembler (Miniasm) and 20% with read-corrected assembler (Canu and Flye) based on 40 threads mode compared to the original Nanopolish. AVAILABILITY AND IMPLEMENTATION: MultiNanopolish is available at GitHub: https://github.com/BioinformaticsCSU/MultiNanopolish. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

NeuralPolish: a novel Nanopore polishing method based on alignment matrix construction and orthogonal Bi-GRU Networks.

MOTIVATION: Oxford Nanopore sequencing producing long reads at low cost has made many breakthroughs in genomics studies. However, the large number of errors in Nanopore genome assembly affect the accuracy of genome analysis. Polishing is a procedure to correct the errors in genome assembly and can improve the reliability of the downstream analysis. However, the performances of the existing polishing methods are still not satisfactory. RESULTS: We developed a novel polishing method, NeuralPolish, to correct the errors in assemblies based on alignment matrix construction and orthogonal Bi-GRU networks. In this method, we designed an alignment feature matrix for representing read-to-assembly alignment. Each row of the matrix represents a read, and each column represents the aligned bases at each position of the contig. In the network architecture, a bi-directional GRU network is used to extract the sequence information inside each read by processing the alignment matrix row by row. After that, the feature matrix is processed by another bi-directional GRU network column by column to calculate the probability distribution. Finally, a CTC decoder generates a polished sequence with a greedy algorithm. We used five real datasets and three assembly tools including Wtdbg2, Flye and Canu for testing, and compared the results of different polishing methods including NeuralPolish, Racon, MarginPolish, HELEN and Medaka. Comprehensive experiments demonstrate that NeuralPolish achieves more accurate assembly with fewer errors than other polishing methods and can improve the accuracy of assembly obtained by different assemblers. AVAILABILITY AND IMPLEMENTATION: https://github.com/huangnengCSU/NeuralPolish.git. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

CLPred: a sequence-based protein crystallization predictor using BLSTM neural network.

MOTIVATION: Determining the structures of proteins is a critical step to understand their biological functions. Crystallography-based X-ray diffraction technique is the main method for experimental protein structure determination. However, the underlying crystallization process, which needs multiple time-consuming and costly experimental steps, has a high attrition rate. To overcome this issue, a series of in silico methods have been developed with the primary aim of selecting the protein sequences that are promising to be crystallized. However, the predictive performance of the current methods is modest. RESULTS: We propose a deep learning model, so-called CLPred, which uses a bidirectional recurrent neural network with long short-term memory (BLSTM) to capture the long-range interaction patterns between k-mers amino acids to predict protein crystallizability. Using sequence only information, CLPred outperforms the existing deep-learning predictors and a vast majority of sequence-based diffraction-quality crystals predictors on three independent test sets. The results highlight the effectiveness of BLSTM in capturing non-local, long-range inter-peptide interaction patterns to distinguish proteins that can result in diffraction-quality crystals from those that cannot. CLPred has been steadily improved over the previous window-based neural networks, which is able to predict crystallization propensity with high accuracy. CLPred can also be improved significantly if it incorporates additional features from pre-extracted evolutional, structural and physicochemical characteristics. The correctness of CLPred predictions is further validated by the case studies of Sox transcription factor family member proteins and Zika virus non-structural proteins. AVAILABILITY AND IMPLEMENTATION: https://github.com/xuanwenjing/CLPred.

DeepSignal: detecting DNA methylation state from Nanopore sequencing reads using deep-learning.

MOTIVATION: The Oxford Nanopore sequencing enables to directly detect methylation states of bases in DNA from reads without extra laboratory techniques. Novel computational methods are required to improve the accuracy and robustness of DNA methylation state prediction using Nanopore reads. RESULTS: In this study, we develop DeepSignal, a deep learning method to detect DNA methylation states from Nanopore sequencing reads. Testing on Nanopore reads of Homo sapiens (H. sapiens), Escherichia coli (E. coli) and pUC19 shows that DeepSignal can achieve higher performance at both read level and genome level on detecting 6 mA and 5mC methylation states comparing to previous hidden Markov model (HMM) based methods. DeepSignal achieves similar performance cross different DNA methylation bases, different DNA methylation motifs and both singleton and mixed DNA CpG. Moreover, DeepSignal requires much lower coverage than those required by HMM and statistics based methods. DeepSignal can achieve 90% above accuracy for detecting 5mC and 6 mA using only 2× coverage of reads. Furthermore, for DNA CpG methylation state prediction, DeepSignal achieves 90% correlation with bisulfite sequencing using just 20× coverage of reads, which is much better than HMM based methods. Especially, DeepSignal can predict methylation states of 5% more DNA CpGs that previously cannot be predicted by bisulfite sequencing. DeepSignal can be a robust and accurate method for detecting methylation states of DNA bases. AVAILABILITY AND IMPLEMENTATION: DeepSignal is publicly available at https://github.com/bioinfomaticsCSU/deepsignal. SUPPLEMENTARY INFORMATION: Supplementary data are available at bioinformatics online.

[Protective effects of Sedum sarmentosum under different soil moisture in CCl4-induced damage in HepG2 cells].

At present, there were few studies about the effects of cultivation measures on the quality and pharmacological activity of medicinal plants. To explore the hepetoprotective activity of Sedum sarmentosum aqueous extracts after different water treatments, S. sarmentosum were planted under five water treatments for 60 days, namely 15%-20% FC (field capacity, S1), 35%-40% FC (S2), 55%-60% FC (S3), 75%-80% FC(S4), and 95%-100% FC (S5) and CCl4 drug-induced liver injury model in vitro was used. Cell viability, cell cycle, and cell apoptosis were individually detected by MTT, PI single staining, and Annexin-V FITC/PI double staining assays. Additionally, ALT, AST and antioxidant index in supernatant were determined by colorimetry. The results showed that, compared with the model group, S. sarmentosum aqueous extract could significantly improve the HepG2 cell viability. Among the five S. sarmentosum groups, the cell viability of S4 (75%-80% FC) treatment was the highest, and the cell apoptosis was the least. Meanwhile, the level of ALT, AST, and MDA in S4 was the lowest, but it achieved the highest level of SOD and GSH. Taken together, different water treatments had great influence on hepatoprotective effect of S. sarmentosum, and the soil moisture of the 75%-80% FC is beneficial to the hepetoprotective activity of S. sarmentosum.

Causal relationship between the gut microbiome and basal cell carcinoma, melanoma skin cancer, ease of skin tanning: evidence from three two-sample mendelian randomisation studies.

Objectives: The present study used publicly available genome-wide association study (GWAS) summary data to perform three two-sample Mendelian randomization (MR) studies, aiming to examine the causal links between gut microbiome and BCC, melanoma skin cancer, ease of skin tanning. Methods: SNPs associated with exposures to basal cell carcinoma, melanoma skin cancer and ease of skin tanning from the genome-wide association study data of UK Biobank and MRC-IEU (MRC Integrative Epidemiology Unit), and the meta-analysis data from Biobank and MRC-IEU were used as instrumental variables (IVs). The casual estimates were assessed with a two-sample Mendelian randomisation test using the inverse-variance-weighted (IVW) method, Wald ratio, MR-Egger method, maximum likelihood, weighted median, simple mode, and weighted mode. Results: After the application of MR analysis, diffirent effects of multiple groups of gut microbiota was observed for BCC, melanoma skin cancer and ease of skin tanning. The relationships between the gut microbiome and BCC, melanoma skin cancer, ease of skin tanning were supported by a suite of sensitivity analyses, with no statistical evidence of instrument heterogeneity or horizontal pleiotropy. Further investigation is required to explore the relationship between between the gut microbiome and BCC, melanoma skin cancer, ease of skin tanning. Conclusion: Our study initially identified potential causal roles between the gut microbiome and BCC, melanoma skin cancer, ease of skin tanning, and highlighted the role of gut microbiome in the progression of basal cell carcinoma, melanoma skin cancer, ease of skin tanning.

Development and validation of a nomogram to predict hypothermia in adult burn patients during escharectomy under general anesthesia.

BACKGROUND: It is very common for burn patients to have hypothermia during escharectomy under general anesthesia, which increases the blood transfusion demand of burn patients, and may lead to blood coagulation disorder or even increase the mortality of patients. It is important to predict the occurrence of hypothermia in advance, but we lack a prognostic prediction model. Our study aimed to develop a nomogram to predict the incidence of hypothermia in adult burn patients undergoing escharectomy under general anesthesia to intervention the hazards associated with hypothermia early. METHODS: This retrospective study included 978 adult burn patients who underwent simple escharectomy under general anesthesia during hospitalization between January 2017 and December 2022, they were further divided into a training cohort and a validation cohort. The clinical data were recorded in electronic medical record system and a self-made collection table of intraoperative hypothermia. The preliminary predictive factors for hypothermia which undergoing simple escharectomy under general anesthesia in burn patients were determined using least absolute shrinkage and selection operator (LASSO) at first, then the final predictive factors determined using binary logistic regression analyses and a nomogram to predict the occurrence of hypothermia was established. The index of concordance(C-index), calibration curves, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) were used to evaluate the performance of the model. RESULTS: A total of 211 patients with hypothermia and 767 patients without hypothermia were selected. Least absolute shrinkage and selection operator regression analysis and binary logistic regression results concluded that burn index, urinary volume, blood transfusion volume and irrigation volume were significantly associated with hypothermia in burn patients undergoing escharectomy under general anesthesia. The nomogram based on these four variables had good predictive efficiency for hypothermia in adult burn patients during escharectomy under general anesthesia, the C-index in the training cohort was 0.903, areas under the receiver operating characteristic curves (AUROC) of for the training cohort (95 % CI 0.877-0.920) and 0.875 for the validation cohort (95 % CI 0.852-0.897) indicated satisfactory discriminative ability of the nomogram, and the calibration curves for the training cohort and the validation cohort also fit as well, indicating that the nomogram had good clinical application value. CONCLUSIONS: Hypothermia in burn patients during escharectomy under general anesthesia is associated with burn index, urinary volume, blood transfusion volume and irrigation volume. We successfully developed a practical nomogram to accurately predict hypothermia, which is a practical method helping clinicians rapidly and conveniently diagnose and guide the treatment of hypothermia in burn patients during escharectomy under general anesthesia.

De novo diploid genome assembly using long noisy reads.

The high sequencing error rate has impeded the application of long noisy reads for diploid genome assembly. Most existing assemblers failed to generate high-quality phased assemblies using long noisy reads. Here, we present PECAT, a Phased Error Correction and Assembly Tool, for reconstructing diploid genomes from long noisy reads. We design a haplotype-aware error correction method that can retain heterozygote alleles while correcting sequencing errors. We combine a corrected read SNP caller and a raw read SNP caller to further improve the identification of inconsistent overlaps in the string graph. We use a grouping method to assign reads to different haplotype groups. PECAT efficiently assembles diploid genomes using Nanopore R9, PacBio CLR or Nanopore R10 reads only. PECAT generates more contiguous haplotype-specific contigs compared to other assemblers. Especially, PECAT achieves nearly haplotype-resolved assembly on B. taurus (Bison×Simmental) using Nanopore R9 reads and phase block NG50 with 59.4/58.0 Mb for HG002 using Nanopore R10 reads.

Efficacy of probiotics or synbiotics in critically ill patients: A systematic review and meta-analysis.

BACKGROUND: This latest systematic review and meta-analysis aim to examine the effects of probiotic and synbiotic supplementation in critically ill patients. METHODS: Relevant articles were retrieved from PubMed, Embase, the Cochrane Database, and the Web of Science. The primary output measure was the incident of ventilator-associated pneumonia, and the secondary outputs were diarrhea, Clostridium diffusion infection (CDI), incident of sepsis, incident of hospital acquired pneumonia, duration of mechanical exploitation, ICU mortality rate, length of ICU stay, in hospital mortality, and length of hospital stay. Data were pooled and expressed as Relative Risk(RR) and Standardized Mean Difference (SMD) with a 95 % confidence interval (CI). RESULTS: 33 studies were included in this systematic review and meta-analysis, with 4065 patients who received probiotics or synbiotics (treatment group) and 3821 patients who received standard care or placebo (control group). The pooled data from all included studies demonstrated that the treatment group has significantly reduced incidence of ventilation-associated pneumonia (VAP) (RR = 0.80; 95 % CI: 0.67-0.96; p = 0.021, I2 = 52.5 %) and sepsis (RR = 0.97; 95 % CI: 0.66-1.42; p = 0.032, I2 = 54.4 %), As well as significantly increased duration of mechanical exploitation (SMD = -0.47; 95 % CI: -0.74-0.20, p = 0.012, I2 = 63.4 %), ICU mobility (RR = 0.95; 95 % CI: 0.71-1.27; p = 0.004, I2 = 62.8 %), length of ICU stay (SMD = -0.29; 95 % CI: -0.58-0.01; p = 0.000, I2 = 82.3 %) and length of hospital stay (SMD = -0.33; 95 % CI: -0.57-0.08, p = 0.000, I2 = 74.2 %) than the control group. There were no significant differences in diarrhea, CDI, incidence of hospital acquired pneumonia, and in hospital mortality between the two groups. CONCLUSION: Our meta-analysis showed that probiotic and synbiotic supplements are beneficial for critically ill patients as they significantly reduce the incidence of ventilator associated pneumonia and sepsis, as well as the duration of mechanical exploitation, length of hospital stay, length of ICU stay, and ICU mortality. However, this intervention has minimal impact on diarrhea, CDI, incidence of hospital acquired pneumonia, and in hospital mortality in critically ill patients.

The role of autonomic nervous system function in hypothermia-mediated sepsis protection.

OBJECTIVE: The objective of this study is to determine whether hypothermia will lessen decreases in heart rate variability and improve outcome in a rat model of sepsis. METHODS: Thirty-six male Sprague-Dawley rats were randomized into 3 groups: control, low sepsis, and high sepsis groups. These groups were each subdivided into a normothermia (37°C) (n = 6) and a hypothermia group (34°C) (n = 6). Cyclophosphamide (100 mg/kg) was administered 5 days before Staphylococcus aureus injection to produce conditions in which sepsis could be induced reliably. Hypothermic rats received temperature reduction for 1 hour post injection. Electrocardiogram was recorded before, after, and 1 day after staphylococcal injection, and the low frequency, high frequency (HF), and LF/HF ratio measurements of heart rate variability and the frequencies of arrhythmia were recorded. The effects of time, sepsis severity, and hypothermia on these variables were analyzed using a multivariate generalized estimation equation mode. RESULTS: Four deaths occurred in the normothermic group, and none, in the hypothermic group. Sepsis of both low and high severity increased low frequency and HF 1 day after sepsis induction. Hypothermia significantly decreased HF in low, but not high sepsis severity. CONCLUSIONS: Hypothermia decreased mortality in septic rats. The influence of hypothermia on HF depended on the severity of the sepsis.

miniBUSCO: a faster and more accurate reimplementation of BUSCO.

Motivation: Assembly completeness evaluation of genome assembly is a critical assessment of the accuracy and reliability of genomic data. An incomplete assembly can lead to errors in gene predictions, annotation, and other downstream analyses. BUSCO is one of the most widely used tools for assessing the completeness of genome assembly by comparing the presence of a set of single-copy orthologs conserved across a wide range of taxa. However, the runtime of BUSCO can be long, particularly for some large genome assemblies. It is a challenge for researchers to quickly iterate the genome assemblies or analyze a large number of assemblies. Results: Here, we present miniBUSCO, an efficient tool for assessing the completeness of genome assemblies. miniBUSCO utilizes the protein-to-genome aligner miniprot and the datasets of conserved orthologous genes from BUSCO. Our evaluation of the real human assembly indicates that miniBUSCO achieves a 14-fold speedup over BUSCO. Furthermore, miniBUSCO reports a more accurate completeness of 99.6% than BUSCO's completeness of 95.7%, which is in close agreement with the annotation completeness of 99.5% for T2T-CHM13. Availability: https://github.com/huangnengCSU/minibusco . Contact: hli@ds.dfci.harvard.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

Psychological status on informal carers for stroke survivors at various phases: a cohort study in China.

Background: In China, the risk of stroke is higher than that in developed countries such as Europe and North America. Informal caregivers play a major role in providing support to stroke survivors. Currently, only limited studies on changes in psychological state of the caregivers at different stages of stroke have been published. Purpose: To investigate the stress and psychological state of informal caregivers of stroke patients in different periods and to explore the factors that affect their states. Methods: 202 informal caregivers of stroke patients were selected in a 3a-grade hospital in Chengdu, Sichuan. Follow-up was conducted by face-to-face interviews, telephone calls, or home visits on days 3, 2 months, and 1 year after onset. We investigated the basic information about the caregivers, including their anxiety, depression and social support conditions. We analyzed the pressure and psychological conditions of informal caregivers at different stages of stroke and analyzed its influencing factors. The data were displayed by the number and percentage of the cases; the continuous variables were described by means and standard deviation. In addition, the data were compared by Pearson correlation analysis and logistic regression analysis. Results: (1) Within 3 days after the onset of stroke, the informal caregivers had the highest stress, the most severe anxiety and depression, the heaviest burden, and the lowest score of medical-social support. Over time, the pressure and burden of the caregivers are gradually decreasing, anxiety and depression are increasing, and social support is also increasing. (2) The stress and psychological status of informal stroke caregivers are affected by multiple factors, including the caregiver's age, relationship with the patient, patient's age, and patient's physical conditions. Conclusion: The stress and psychological status of informal caregivers varied in the different stages of stroke, and they were affected by several factors. Medical staff should pay attention to informal caregivers while providing care for patients. Relevant interventions may be developed based on the results to improve the health of informal caregivers and thus to promote the health of patients.

DNA 5-methylcytosine detection and methylation phasing using PacBio circular consensus sequencing.

Long single-molecular sequencing technologies, such as PacBio circular consensus sequencing (CCS) and nanopore sequencing, are advantageous in detecting DNA 5-methylcytosine in CpGs (5mCpGs), especially in repetitive genomic regions. However, existing methods for detecting 5mCpGs using PacBio CCS are less accurate and robust. Here, we present ccsmeth, a deep-learning method to detect DNA 5mCpGs using CCS reads. We sequence polymerase-chain-reaction treated and M.SssI-methyltransferase treated DNA of one human sample using PacBio CCS for training ccsmeth. Using long (≥10 Kb) CCS reads, ccsmeth achieves 0.90 accuracy and 0.97 Area Under the Curve on 5mCpG detection at single-molecule resolution. At the genome-wide site level, ccsmeth achieves >0.90 correlations with bisulfite sequencing and nanopore sequencing using only 10× reads. Furthermore, we develop a Nextflow pipeline, ccsmethphase, to detect haplotype-aware methylation using CCS reads, and then sequence a Chinese family trio to validate it. ccsmeth and ccsmethphase can be robust and accurate tools for detecting DNA 5-methylcytosines.

SACall: A Neural Network Basecaller for Oxford Nanopore Sequencing Data Based on Self-Attention Mechanism.

Highly portable Oxford Nanopore sequencer producing long reads in real-time at low cost has made many breakthroughs in genomics studies. However, a major limitation of nanopore sequencing is its high errors when deciphering DNA sequences from noisy and complex raw data. In this paper, we developed an end-to-end basecaller, SACall, based on convolution layers, transformer self-attention layers and a CTC decoder. In SACall, the convolution layers are used to downsample the signals and capture the local patterns. To achieve the contextual relevance of signals, self-attention layers are adopted to calculate the similarity of the signals at any two positions in the raw signal sequence. Finally, the CTC decoder generates the DNA sequence by a beam search algorithm. We use a benchmark consisting of nine isolated genomes to test the quality of different basecallers including SACall, Albacore, and Guppy. The performances of basecallers are evaluated from the perspective of read accuracy, assembly quality, and consensus accuracy. Among most of the genomes in the test benchmark, the reads basecalled by SACall have fewer errors than the reads basecalled by other basecallers. When assembling the basecalled reads of each genome, the assembly from SACall basecalled reads achieves a higher assembly identity. In addition, there are fewer errors in the polished assembly from reads basecalled by SACall compared to those basecalled by Albacore and Guppy. In general, SACall outperforms the Nanopore official basecallers Albacore and Guppy in the benchmark. Moreover, SACall is an open-source and freely available basecaller, which gives a chance for researchers to train their own basecalling models on specific data and basecall Nanopore reads.