Construction of mitochondrial quality regulation genes-related prognostic model based on bulk-RNA-seq analysis in multiple myeloma.

Mitochondrial quality regulation plays an important role in affecting the treatment sensitivity of multiple myeloma (MM). We aimed to develop a mitochondrial quality regulation genes (MQRGs)-related prognostic model for MM patients. The Genomic Data Commons-MM of bulk RNA-seq, mutation, and single-cell RNA-seq (scRNA-seq) dataset were downloaded, and the MQRGs gene set was collected previous study. "maftools" and CIBERSORT were used for mutation and immune-infiltration analysis. Subsequently, the "ConsensusClusterPlus" was used to perform the unsupervised clustering analysis, "survminer" and "ssGSEA" R package was used for the Kaplan-Meier survival and enrichment analysis, "limma" R, univariate and Least Absolute Shrinkage and Selection Operator Cox were used for RiskScore model. The "timeROC" R package was used for Receiver Operating Characteristic Curve analysis. Finally, the "Seurat" R package was used for scRNA-seq analysis. These MQRGs are mainly located on chromosome-1,2,3,7, and 22 and had significant expression differences among age, gender, and stage groups, in which PPARGC1A and PPARG are the high mutation genes. Most MQRGs expression are closely associated with the plasma cells infiltration and can divide the patients into 2 different prognostic clusters (C1, C2). Then, 8 risk models were screened from 60 DEGs for RiskScore, which is an independent prognostic factor and effectively divided the patients into high and low risk groups with significant difference of immune checkpoint expression. Nomogram containing RiskScore can accurately predict patient prognosis, and a series of specific transcription factor PRDM1 and IRF1 were identified. We described the based molecular features and developed a high effective MQRGs-related prognostic model in MM.

[Immune-related severe pneumonia: A case report].

With the continuous development and maturity of anti-tumor immunotherapy technology, immune checkpoint inhibitors as one of the main methods of immunotherapy were increasingly widely used in clinical tumor cases, bringing new hope for many advanced cancer patients with poor response to traditional treatment, but at the same time, reported on adverse reactions of various organs related to this were also increasing, and the immune damage caused by them was harmful to patients, especially immune checkpoint inhibitor-associated pneumonia, immune checkpoint inhibitor-associated myocarditis and immune checkpoint inhibitor-associated encephalitis, which could even seriously endangered the lives of patients. Therefore, it was necessary for clinicians to fully understand and master the mechanism, clinical characteristics, laboratory and imaging examination characteristics, diagnostic criteria and differential diagnosis conditions, and treatment principles of adverse reactions that may be caused by immune checkpoint inhibitors, so as to find a more optimized anti-tumor treatment regimen and actively prepared for the treatment of possible immune-related adverse reactions. In this paper, we reported a case of immune checkpoint inhibitor-associated severe pneumonia, referred to the relevant guidelines, introduced its clinical features, laboratory and imaging findings, difficulties encountered in the diagnosis and treatment process, briefly analyzed the causes, and reviewed the possibility of immune-related pneumonia should be considered when respiratory symptoms occurred in patients receiving immunotherapy; the increased ratio of blood neutrophil count to lymphocyte count, and the increased ratio of eosinophil count to lymphocyte count could be used as indicators to indicate immune-related adverse reactions in patients; bronchoalveolar lavage fluid examination and bronchoscopy and lung biopsy were helpful for the diagnosis; when immune checkpoint inhibitor-associated severe pneumonia occurred, in addition to symptomatic and sup-portive treatment, adequate glucocorticoid-based immunosuppressive therapy should be given in time, and combined with cytokines monoclonal antibodies and other biological agents, immunoglobulin co-therapy, but the current indications for the use of biological agents were not fully clear, and the use of high-dose immunosuppressive drugs might cause the risk of severe infection. Therefore, according to the relevant literature and the findings in the process of clinical diagnosis and treatment, this paper proposed that the serum levels of IL-6, TNF-α, CRP and other inflammatory mediators in patients may be used as a quantitative indication to initiate biological agent therapy and accumulate experience for better solving similar problems in the future.

Evaluation of Four Forensic Investigative Genetic Genealogy Analysis Approaches with Decreased Numbers of SNPs and Increased Genotyping Errors.

Background: Forensic investigative genetic genealogy (FIGG) has developed rapidly in recent years and is considered a novel tool for crime investigation. However, crime scene samples are often of low quality and quantity and are challenging to analyze. Deciding which approach should be used for kinship inference in forensic practice remains a troubling problem for investigators. Methods: In this study, we selected four popular approaches-KING, IBS, TRUFFLE, and GERMLINE-comprising one method of moment (MoM) estimator and three identical by descent (IBD) segment-based tools and compared their performance at varying numbers of SNPs and levels of genotyping errors using both simulated and real family data. We also explored the possibility of making robust kinship inferences for samples with ultra-high genotyping errors by integrating MoM and the IBD segment-based methods. Results: The results showed that decreasing the number of SNPs had little effect on kinship inference when no fewer than 164 K SNPs were used for all four approaches. However, as the number decreased further, decreased efficiency was observed for the three IBD segment-based methods. Genotyping errors also had a significant effect on kinship inference, especially when they exceeded 1%. In contrast, MoM was much more robust to genotyping errors. Furthermore, the combination of the MoM and the IBD segment-based methods showed a higher overall accuracy, indicating its potential to improve the tolerance to genotyping errors. Conclusions: In conclusion, this study shows that different approaches have unique characteristics and should be selected for different scenarios. More importantly, the integration of the MoM and the IBD segment-based methods can improve the robustness of kinship inference and has great potential for applications in forensic practice.

Epigenetic regulation of global proteostasis dynamics by RBBP5 ensures mammalian organismal health.

Proteostasis is vital for cellular health, with disruptions leading to pathologies including aging, neurodegeneration and metabolic disorders. Traditionally, proteotoxic stress responses were studied as acute reactions to various noxious factors; however, recent evidence reveals that many proteostasis stress-response genes exhibit ~12-hour ultradian rhythms under physiological conditions in mammals. These rhythms, driven by an XBP1s-dependent 12h oscillator, are crucial for managing proteostasis. By exploring the chromatin landscape of the murine 12h hepatic oscillator, we identified RBBP5, a key subunit of the COMPASS complex writing H3K4me3, as an essential epigenetic regulator of proteostasis. RBBP5 is indispensable for regulating both the hepatic 12h oscillator and transcriptional response to acute proteotoxic stress, acting as a co-activator for proteostasis transcription factor XBP1s. RBBP5 ablation leads to increased sensitivity to proteotoxic stress, chronic inflammation, and hepatic steatosis in mice, along with impaired autophagy and reduced cell survival in vitro. In humans, lower RBBP5 expression is associated with reduced adaptive stress-response gene expression and hepatic steatosis. Our findings establish RBBP5 as a central regulator of proteostasis, essential for maintaining mammalian organismal health.

Hybrid Optimization Path Planning Method for AGV Based on KGWO.

To address the path planning problem for automated guided vehicles (AGVs) in challenging and complex industrial environments, a hybrid optimization approach is proposed, integrating a Kalman filter with grey wolf optimization (GWO), as well as incorporating partially matched crossover (PMX) mutation operations and roulette wheel selection. Paths are first optimized using GWO, then refined with Kalman filter corrections every ten iterations. Moreover, roulette wheel selection guides robust parent path selection, while an elite strategy and partially matched crossover (PMX) with mutation generate diverse offspring. Extensive simulations and experiments were carried out under a densely packed goods scenario and complex indoor layout scenario, within a fully automated warehouse environment. The results showed that this hybrid method not only enhanced the various optimization metrics but also ensured more predictable and collision-free navigation paths, particularly in environments with complex obstacles. These improvements lead to increased operational efficiency and safety, highlighting the method's potential in real-world applications.

Using anthropometric parameters to predict insulin resistance among patients without diabetes mellitus.

Anthropometric parameters are widely used in the clinical assessment of hypertension, type 2 diabetes, and cardiovascular disease. However, few studies have compared the association between different anthropometric parameters and insulin resistance (IR). This study was aimed at investigating the relationship between 6 indicators, including body mass index (BMI), calf circumference (CC), arm circumference (AC), thigh circumference (TC), waist circumference (WC), waist-height ratio (WHtR), and IR. Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) was used to measure IR. Weighted linear regression was used to assess the relationship between different parameters and IR. The receiver operating characteristic curve (ROC) was employed to compare the strength of the relationship between different anthropometric parameters and IR. A total of 8069 participants were enrolled in our study, including 4873 without IR and 3196 with IR. The weighted linear regression results showed that BMI, CC, AC, TC and WC were significantly correlated with IR, except WHtR. After adjusting for multiple confounding factors, we found that BMI, AC and WC were significantly positively correlated with IR, while TC was significantly negatively correlated with IR. Logistic regression results showed that a larger TC was associated with a decreased risk of IR. In addition, BMI and WC had similar areas under the curve (AUC: 0.780, 95% CI 0.770-0.790; AUC: 0.774, 95% CI 0.763-0.784, respectively), which were higher than TC and AC (AUC: 0.698, 95% CI 0.687-0.710, AUC: 0.746, 95% CI 0.735-0.757, respectively). To our knowledge, this is the first study to report a negative correlation between TC and IR among patients without diabetes mellitus. Therefore, TC may be a new tool to guide public health and a clinical predictor of IR in non-diabetic patients.

Inference of forensic body fluids/tissues based on mitochondrial DNA copy number: a preliminary study.

The inference of body fluids and tissues is critical in reconstructing crime scenes and inferring criminal behaviors. Nevertheless, present methods are incompatible with conventional DNA genotyping, and additional testing might result in excessive consumption of forensic scene materials. This study aims to investigate the feasibility of distinguishing common body fluids/tissues through the difference in mitochondrial DNA copy number (mtDNAcn). Four types of body fluids/tissues were analyzed in this study - hair, saliva, semen, and skeletal muscle. MtDNAcn was estimated by dividing the read counts of mitochondrial DNA to that of nuclear DNA (RRmt/nu). Results indicated that there were significant differences in RRmt/nu between different body fluids/tissues. Specifically, hair samples exhibited the highest RRmt/nu (log10RRmt/nu: 4.3 ± 0.28), while semen samples showed the lowest RRmt/nu (log10RRmt/nu: -0.1 ± 0.28). RRmt/nu values for DNA samples without extraction were notably higher (approximately 2.9 times) than those obtained after extraction. However, no significant difference in RRmt/nu was observed between various age and gender groups. Hierarchical clustering and Kmeans clustering analyses showed that body fluids/tissues of the same type clustered closely to each other and could be inferred with high accuracy. In conclusion, this study demonstrated that the simultaneous detection of nuclear and mitochondrial DNA made it possible to perform conventional DNA analyses and body fluid/tissue inference at the same time, thus killing two birds with one stone. Furthermore, mtDNAcn has the potential to serve as a novel and promising biomarker for the identification of body fluids/tissues.

Utility analyses of AVITI sequencing chemistry.

BACKGROUND: DNA sequencing is a critical tool in modern biology. Over the last two decades, it has been revolutionized by the advent of massively parallel sequencing, leading to significant advances in the genome and transcriptome sequencing of various organisms. Nevertheless, challenges with accuracy, lack of competitive options and prohibitive costs associated with high throughput parallel short-read sequencing persist. RESULTS: Here, we conduct a comparative analysis using matched DNA and RNA short-reads assays between Element Biosciences' AVITI and Illumina's NextSeq 550 chemistries. Similar comparisons were evaluated for synthetic long-read sequencing for RNA and targeted single-cell transcripts between the AVITI and Illumina's NovaSeq 6000. For both DNA and RNA short-read applications, the study found that the AVITI produced significantly higher per sequence quality scores. For PCR-free DNA libraries, we observed an average 89.7% lower experimentally determined error rate when using the AVITI chemistry, compared to the NextSeq 550. For short-read RNA quantification, AVITI platform had an average of 32.5% lower error rate than that for NextSeq 550. With regards to synthetic long-read mRNA and targeted synthetic long read single cell mRNA sequencing, both platforms' respective chemistries performed comparably in quantification of genes and isoforms. The AVITI displayed a marginally lower error rate for long reads, with fewer chemistry-specific errors and a higher mutation detection rate. CONCLUSION: These results point to the potential of the AVITI platform as a competitive candidate in high-throughput short read sequencing analyses when juxtaposed with the Illumina NextSeq 550.

Risk Factors for Depression in Patients With Knee Osteoarthritis: A Systematic Review and Meta-analysis.

BACKGROUND: Knee osteoarthritis (KOA) is a widespread chronic condition. Depression frequently occurs among patients with KOA. The objective of this meta-analysis was to identify risk factors associated with comorbid depression in patients with KOA. MATERIALS AND METHODS: A comprehensive search of the PubMed/MEDLINE, Embase, Cochrane Library, and Web of Science databases was conducted for studies related to comorbid depression in patients with KOA. We conducted statistical analyses to obtain relevant results, followed by heterogeneity tests and assessment for publication bias. RESULTS: The prevalence of comorbid depression among patients with KOA was 34% (95% CI, 28%-41%). Notable risk factors linked to comorbid depression in patients with KOA included female sex (relative risk [RR], 1.17; 95% CI, 1.11-1.23), obesity (mean difference [MD], 1.30; 95% CI, 0.88-1.71), use of analgesics (RR, 1.50; 95% CI, 1.38-1.63), comorbidities (MD, 0.20; 95% CI, 0.10-0.31), unmarried or widowed status (RR, 1.72; 95% CI, 1.56-1.91), bilateral knee pain (RR, 1.38; 95% CI, 1.11-1.71), high total Western Ontario and Mc-Master Universities Arthritis Index (WOMAC) score (MD, 14.92; 95% CI, 10.02-19.82), high WOMAC pain score (MD, 5.76; 95% CI, 2.86-8.67), low gait velocity (MD, -0.12; 95% CI, -0.16 to -0.09), and extended duration in the Timed Up and Go Test (MD, 1.56; 95% CI, 0.87-2.25). CONCLUSION: Based on the current evidence, female sex, obesity, use of analgesics, comorbidities, unmarried or widowed status, bilateral knee pain, high total WOMAC score, high WOMAC pain score, low gait velocity, and prolonged time on the Timed Up and Go Test were identified as risk factors for depression in patients with KOA. Focus should be given to these aspects when preventing depression among these patients. [Orthopedics. 2024;47(5):e225-e232.].

A study on factors related to sleep disorders and serum BDNF expression levels in patients with primary SjÓ§gren's syndrome.

OBJECTIVES: We aimed to assess the sleep quality of patients with primary Sjögren's syndrome (pSS) and the associated factors. Moreover, Preliminary exploration of the clinical significance of serum brain-derived neurotrophic factor (BDNF) in pSS patients with sleep disorders. METHODS: A self-report survey was administered to 111 pSS patients and 40 healthy individuals using the Pittsburgh Sleep Quality Index (PSQI) for sleep quality. General clinical information,the sleep quality and mental conditions were collected using on-site questionnaires and various scales. 40 healthy controls from the health examination center of the same hospital, who were age and sex matched. Detection of serum BDNF levels by ELISA method . Independent samples t tests, Chi-square analysis, logistic regression were used to analyze these data. RESULTS: Patients with pSS had higher scores on the PSQI than the healthy individuals. Abnormal sweating, high PHQ-9 and ESSPRI scores were independent risk factors for sleep disorders. pSS patients had lower serum BDNF than the healthy individuals, The area under the curve (AUC) of predicting sleep disorder in pSS patients using detection of serum BDNF level was 0.8470, and the sensitivity and specificity were 0.951 and 0.727, which were superior to PHQ-9 and GAD-7. CONCLUSION: Compared with the healthy individuals, pSS patients had a higher prevalence of sleep disorders and lower serum BNDF. Serum BDNF level demonstrated greater predictive advantage for sleep disorder in pSS patients.

Impact of different CEBPA mutations on therapeutic outcome in acute myeloid leukemia.

Biallelic mutations of the CEBPA gene (CEBPAbi) are generally associated with favorable prognosis in patients with acute myeloid leukemia (AML). Monoallelic mutations of the CEBPA gene in carboxy-terminal DNA-binding region (CEBPAsmbZIP) and amino-terminal transactivation domains (CEBPAsmTAD) indicate distinct clinical characteristics and therapeutic outcomes. However, further investigation is required to fully understand these differences. In this retrospective study, we enrolled 77 AML patients with CEBPA mutations, including 53 with CEBPAbi, 12 with CEBPAsmbZIP and 12 with CEBPAsmTAD. The clinical characteristics of the three CEBPAmut groups presented significant differences in age, FAB classification, hemoglobin level and platelet count at diagnosis. The CEBPAsmTAD group exhibited shorter 2-year overall survival (OS) and relapse-free survival (RFS) compared to the CEBPAbi group and CEBPAsmbZIP group in AML patients. The most common co-mutations observed in CEBPAmut AML patients were TET2 and GATA2, which had no effect on prognosis. 2-year RFS of 27 CEBPAmut AML patients who underwent allo-HSCT was better than those who did not. MRD3 positive was identified as an influencing factor for 2-year OS and RFS. Allo-HSCT was found to improve the prognosis of CEPBAmut AML patients with positive MRD3 and adverse co-mutations.

Analysing substitutions in recent World Cups and European Championships in male and female elite football - influence of new substitution rules.

Substitutions play a key role in modern football and can substantially affect the physical and overall performance of a team, and the recent substitution rule changes are worth investigating. This study explored the characteristics of substitutions, including different substitution rules, game results, sex, competition stages, tournaments and penalty shoot-outs success rates. We analysed data from a total of 3,738 substitutions from the last 10 years (2013-2023) of European Championships and World Cups, both men's and women's games. Non-parametric tests and chi-square tests were used for statistical analysis with the significance level set at p < 0.05. With the 5-substitution rule, 48% more substitutions occurred compared to the 3-substitution rule (4.26 ± 1.07 vs. 2.87 ± 0.43, p < 0.05) with a slight increase in the average substitution time (70.6 ± 14.3 vs. 69.2 ± 14.6 min, p < 0.05), and 10% more substitutions in the men's game compared to the women's game (p < 0.05). The timing of the first substitution was slightly different in the knock-out stage compared to group stage (59.8 ± 14.7 vs. 57.2 ± 13.3 min, p < 0.05), and the timing for the winning team and drawing team was later than for the losing team (p < 0.05). A total of 13.2% goals were scored by substitutes, with no significant difference between the 5-substitution rule (15.9%) vs the 3-substition rule (12.5%) (p > 0.05). Interestingly, substitute players had a lower success rate in penalty shoot-out compared to starters (61 vs. 74%, p < 0.05). Additionally, substitute player goal scorers entered the pitch later (p < 0.05) in male games compared to female games and in knock-out stage games compared to group games. This study highlights the importance of substitution rules and timing in modern elite football matches. The timing of the first substitution, introduction of substitutes in knock-out stages, and a lower success rate of substitute players in penalty shoot-outs are crucial factors to consider. Coaches can use this information to make strategic substitution decisions to improve team performance.

"I feel like I'm walking on eggshells": a qualitative study of moral distress among Chinese emergency doctors.

BACKGROUND: While the number of emergency patients worldwide continues to increase, emergency doctors often face moral distress. It hampers the overall efficiency of the emergency department, even leading to a reduction in human resources. AIM: This study explored the experience of moral distress among emergency department doctors and analyzed the causes of its occurrence and the strategies for addressing it. METHOD: Purposive and snowball sampling strategies were used in this study. Data were collected through in-depth, semi-structured interviews with 10 doctors working in the emergency department of a tertiary general hospital in southwest China. The interview data underwent processing using the Nvivo 14 software. The data analysis was guided by Colaizzi's phenomenological analysis method. STUDY FINDINGS: This study yielded five themes: (1) imbalance between Limited Medical Resources and High-Quality Treatment Needs; (2) Ineffective Communication with Patients; (3) Rescuing Patients With no prospect of treatment; (4) Challenges in Sustaining Optimal Treatment Measures; and (5) Strategies for Addressing Moral Distress. CONCLUSION: The moral distress faced by emergency doctors stems from various aspects. Clinical management and policymakers can alleviate this distress by enhancing the dissemination of emergency medical knowledge to the general public, improving the social and economic support systems, and strengthening multidisciplinary collaboration and doctors' communication skills.

The impact of social participation on the health status of the older adult: An empirical study based on CGSS 2021 data.

INTRODUCTION: With the rapid pace of population aging, the health issues of the older adult have garnered widespread attention. Social participation plays a pivotal role in the health of the older adult. This study aims to explore the impact of social participation on the health status of the older adult. METHODS: Using a binary logistic regression model, this study analyzes the influence of social participation methods on the health status of older adult individuals in China based on cross-sectional data from the "China Comprehensive Social Survey" in 2021. The study sample comprises individuals aged 60 to 99 years. RESULTS: It was found that participation in physical activities [P<0.001, OR = 1.907], social and recreational activities [P<0.001, OR = 1.387], and online activities [P<0.001, OR = 1.808] were significantly positively correlated with the health status of the older adult. CONCLUSIONS: The health of older adults is influenced by a combination of physical activities, social and recreational activities, and online activities. Good health is closely associated with high levels of physical activity. Engaging in physical exercise promotes physiological health, while participating in social and recreational activities has a significant impact on cognitive and depressive states. Additionally, involvement in online activities helps alleviate feelings of loneliness and enhances overall well-being. RECOMMENDATIONS: 1)Promote the development of physical activities for the older adult: Create an integrated environment for physical exercise. 2)Expand the social circle of the older adult: Construct diverse and structured communities to enhance well-being. 3)Develop online activities for the older adult: Facilitate their integration into the digital age. 4)Foster interdisciplinary collaboration for older adult health: Build partnerships across various domains to promote older adult health.

NEATmap: a high-efficiency deep learning approach for whole mouse brain neuronal activity trace mapping.

Quantitative analysis of activated neurons in mouse brains by a specific stimulation is usually a primary step to locate the responsive neurons throughout the brain. However, it is challenging to comprehensively and consistently analyze the neuronal activity trace in whole brains of a large cohort of mice from many terabytes of volumetric imaging data. Here, we introduce NEATmap, a deep learning-based high-efficiency, high-precision and user-friendly software for whole-brain neuronal activity trace mapping by automated segmentation and quantitative analysis of immunofluorescence labeled c-Fos+ neurons. We applied NEATmap to study the brain-wide differentiated neuronal activation in response to physical and psychological stressors in cohorts of mice.

Improved individual identification in DNA mixtures of unrelated or related contributors through massively parallel sequencing.

DNA mixtures are a common sample type in forensic genetics, and we typically assume that contributors to the mixture are unrelated when calculating the likelihood ratio (LR). However, scenarios involving mixtures with related contributors, such as in family murder or incest cases, can also be encountered. Compared to the mixtures with unrelated contributors, the kinship within the mixture would bring additional challenges for the inference of the number of contributors (NOC) and the construction of probabilistic genotyping models. To evaluate the influence of potential kinship on the individual identification of the person of interest (POI), we conducted simulations of two-person (2 P) and three-person (3 P) DNA mixtures containing unrelated or related contributors (parent-child, full-sibling, and uncle-nephew) at different mixing ratios (for 2 P: 1:1, 4:1, 9:1, and 19:1; for 3 P: 1:1:1, 2:1:1, 5:4:1, and 10:5:1), and performed massively parallel sequencing (MPS) using MGIEasy Signature Identification Library Prep Kit on MGI platform. In addition, in silico simulations of mixtures with unrelated and related contributors were also performed. In this study, we evaluated 1): the MPS performance; 2) the influence of multiple genetic markers on determining the presence of related contributors and inferring the NOC within the mixture; 3) the probability distribution of MAC (maximum allele count) and TAC (total allele count) based on in silico mixture profiles; 4) trends in LR values with and without considering kinship in mixtures with related and unrelated contributors; 5) trends in LR values with length- and sequence-based STR genotypes. Results indicated that multiple numbers and types of genetic markers positively influenced kinship and NOC inference in a mixture. The LR values of POI were strongly dependent on the mixing ratio. Non- and correct-kinship hypotheses essentially did not affect the individual identification of the major POI; the correct kinship hypothesis yielded more conservative LR values; the incorrect kinship hypothesis did not necessarily lead to the failure of POI individual identification. However, it is noteworthy that these considerations could lead to uncertain outcomes in the identification of minor contributors. Compared to length-based STR genotyping, using sequence-based STR genotype increases the individual identification power of the POI, concurrently improving the accuracy of mixing ratio inference using EuroForMix. In conclusion, the MGIEasy Signature Identification Library Prep kit demonstrated robust individual identification power, which is a viable MPS panel for forensic DNA mixture interpretations, whether involving unrelated or related contributors.

IFDlong: an isoform and fusion detector for accurate annotation and quantification of long-read RNA-seq data.

Advancements in long-read transcriptome sequencing (long-RNA-seq) technology have revolutionized the study of isoform diversity. These full-length transcripts enhance the detection of various transcriptome structural variations, including novel isoforms, alternative splicing events, and fusion transcripts. By shifting the open reading frame or altering gene expressions, studies have proved that these transcript alterations can serve as crucial biomarkers for disease diagnosis and therapeutic targets. In this project, we proposed IFDlong, a bioinformatics and biostatistics tool to detect isoform and fusion transcripts using bulk or single-cell long-RNA-seq data. Specifically, the software performed gene and isoform annotation for each long-read, defined novel isoforms, quantified isoform expression by a novel expectation-maximization algorithm, and profiled the fusion transcripts. For evaluation, IFDlong pipeline achieved overall the best performance when compared with several existing tools in large-scale simulation studies. In both isoform and fusion transcript quantification, IFDlong is able to reach more than 0.8 Spearman's correlation with the truth, and more than 0.9 cosine similarity when distinguishing multiple alternative splicing events. In novel isoform simulation, IFDlong can successfully balance the sensitivity (higher than 90%) and specificity (higher than 90%). Furthermore, IFDlong has proved its accuracy and robustness in diverse in-house and public datasets on healthy tissues, cell lines and multiple types of diseases. Besides bulk long-RNA-seq, IFDlong pipeline has proved its compatibility to single-cell long-RNA-seq data. This new software may hold promise for significant impact on long-read transcriptome analysis. The IFDlong software is available at https://github.com/wenjiaking/IFDlong.

The Effect of Low HBV-DNA Viral Load on Recurrence in Hepatocellular Carcinoma Patients Who Underwent Primary Locoregional Treatment and the Development of a Nomogram Prediction Model.

(1) Background: HBV-DNA is an essential clinical indicator of primary hepatocellular carcinoma (HCC) prognosis. Our study aimed to investigate the prognostic implication of a low load of HBV-DNA in HCC patients who underwent local treatment. Additionally, we developed and validated a nomogram to predict the recurrence of patients with low (20-100 IU/mL) viral loads (L-VL). (2) Methods: A total of 475 HBV-HCC patients were enrolled, including 403 L-VL patients and 72 patients with very low (<20 IU/mL) viral loads (VL-VL). L-VL HCC patients were randomly divided into a training set (N = 282) and a validation set (N = 121) at a ratio of 7:3. Utilizing the Lasso-Cox regression analysis, we identified independent risk factors for constructing a nomogram. (3) Results: L-VL patients had significantly shorter RFS than VL-VL patients (38.2 m vs. 23.4 m, p = 0.024). The content of the nomogram included gender, BCLC stage, Glob, and MLR. The C-index (0.682 vs. 0.609); 1-, 3-, and 5-year AUCs (0.729, 0.784, and 0.783, vs. 0.631, 0.634, the 0.665); calibration curves; and decision curve analysis (DCA) curves of the training and validation cohorts proved the excellent predictive performance of the nomogram. There was a statistically significant difference in RFS between the low-, immediate-, and high-risk groups both in the training and validation cohorts (p < 0.001); (4) Conclusions: Patients with L-VL had a worse prognosis. The nomogram developed and validated in this study has the advantage of predicting patients with L-VL.

High-Voltage Cable Buffer Layer Ablation Fault Identification Based on Artificial Intelligence and Frequency Domain Impedance Spectroscopy.

In recent years, the occurrence of high-voltage cable buffer layer ablation faults has become frequent, posing a serious threat to the safe and stable operation of cables. Failure to promptly detect and address such faults may lead to cable breakdowns, impacting the normal operation of the power system. To overcome the limitations of existing methods for identifying buffer layer ablation faults in high-voltage cables, a method for identifying buffer layer ablation faults based on frequency domain impedance spectroscopy and artificial intelligence is proposed. Firstly, based on the cable distributed parameter model and frequency domain impedance spectroscopy, a mathematical model of the input impedance of a cable containing buffer layer ablation faults is derived. Through a simulation, the input impedance spectroscopy at the first end of the cables under normal conditions, buffer layer ablation, local aging, and inductive faults is performed, enabling the identification of inductive and capacitive faults through a comparative analysis. Secondly, the frequency domain amplitude spectroscopy of the buffer layer ablation and local aging faults are used as datasets and are input into a neural network model for training and validation to identify buffer layer ablation and local aging faults. Finally, using multiple evaluation metrics to assess the neural network model validates the superiority of the MLP neural network in cable fault identification models and experimentally confirms the effectiveness of the proposed method.