Active Fabrics with Controllable Stiffness for Robotic Assistive Interfaces.

Assistive interfaces enable collaborative interactions between humans and robots. In contrast to traditional rigid devices, conformable fabrics with tunable mechanical properties have emerged as compelling alternatives. However, existing assistive fabrics actuated by fluidic or thermal stimuli struggle to adapt to complex body contours and are hindered by challenges such as large volumes after actuation and slow response rates. To overcome these limitations, we draw inspiration from biological protective organisms combining hard and soft phases, and propose active assistive fabrics consisting of architectured rigid tiles interconnected with flexible actuated fibers. Through programmable tessellation of target body shapes into architectured tiles and controlling their interactions by the actuated fibers, our active fabrics can rapidly (within seconds) transition between soft compliant configurations and rigid states conformable to the body (> 350 times stiffness change, loading capacity to weight ratio > 50) while minimizing the device volume after actuation. We demonstrate the versatility of our active fabrics as exosuits for tremor suppression and lifting assistance. We also present its potential as body armors for impact mitigation. Electrothermal actuators are integrated for smart actuation with convenient folding capabilities. Our work offers a practical framework for designing customizable active fabrics with shape adaptivity and controllable stiffness, these active fabrics have wide applications in wearable exosuits, haptic devices, and medical rehabilitation systems. This article is protected by copyright. All rights reserved.

TORSEL, a 4EBP1-based mTORC1 live-cell sensor, reveals nutrient-sensing targeting by histone deacetylase inhibitors.

BACKGROUND: Mammalian or mechanistic target of rapamycin complex 1 (mTORC1) is an effective therapeutic target for diseases such as cancer, diabetes, aging, and neurodegeneration. However, an efficient tool for monitoring mTORC1 inhibition in living cells or tissues is lacking. RESULTS: We developed a genetically encoded mTORC1 sensor called TORSEL. This sensor changes its fluorescence pattern from diffuse to punctate when 4EBP1 dephosphorylation occurs and interacts with eIF4E. TORSEL can specifically sense the physiological, pharmacological, and genetic inhibition of mTORC1 signaling in living cells and tissues. Importantly, TORSEL is a valuable tool for imaging-based visual screening of mTORC1 inhibitors. Using TORSEL, we identified histone deacetylase inhibitors that selectively block nutrient-sensing signaling to inhibit mTORC1. CONCLUSIONS: TORSEL is a unique living cell sensor that efficiently detects the inhibition of mTORC1 activity, and histone deacetylase inhibitors such as panobinostat target mTORC1 signaling through amino acid sensing.

Exploration of the mechanism of Traditional Chinese Medicine for anxiety and depression in patients with diarrheal irritable bowel syndrome based on network pharmacology and meta-analysis.

Background: The efficacy of Chinese herbal medicine (CHM) in managing irritable bowel syndrome with diarrhea (IBS-D) accompanied by anxiety and depression remains uncertain. Thus, a systematic review was carried out employing meta-analysis and network pharmacology to ascertain the efficacy and underlying mechanisms of CHM therapy. Methods: By conducting a systematic review, including literature search, screening, and data extraction, we identified 25 randomized controlled trials to assess CHM's effectiveness in treating irritable bowel syndrome alongside anxiety and depression. Network pharmacology was utilized to scrutinize the metabolite utility of CHM in addressing this condition. Potential primary mechanisms were synthesized using information sourced from the PubMed database. Results: Twenty-five studies, including 2055 patients, were analyzed, revealing significant treatment efficacy for IBS-D in the trial group compared to controls [OR = 4.01, 95% CI (2.99, 5.36), I2 = 0%] Additionally, treatment for depression [SMD = -1.08, 95% CI (-1.30, -0.86), p < 0.00001, I2 = 68%; SDS: SMD = -1.69, 95% CI (-2.48, -0.90), p < 0.0001, I2 = 96%] and anxiety [HAMA: SMD = -1.29, 95% CI (-1.68, -0.91), p < 0.00001, I2 = 89%; SAS: SMD = -1.75, 95% CI (-2.55, -0.95), p < 0.00001, I2 = 96%] significantly improved in the trial group. Furthermore, the trial group exhibited a significantly lower disease relapse rate [OR = 0.30, 95% CI (0.20, 0.44), p < 0.00001, I2 = 0%]. CHM treatment consistently improved IBS severity (IBS-SSS) and symptom scores. Network pharmacology analysis identified key chemical metabolites in traditional Chinese medicine formulations, including Beta-sitosterol, Stigmasterol, Quercetin, Naringenin, Luteolin, Kaempferol, Nobiletin, Wogonin, Formononetin, and Isorhamnetin. Utilizing the STRING database and Cytoscape v3.9.0 software, a protein-protein interaction (PPI) network revealed the top eight key targets: IL-6, TNF, PPARG, PTGS2, ESR1, NOS3, MAPK8, and AKT1, implicated in anti-inflammatory responses, antioxidant stress modulation, and neurotransmitter homeostasis maintenance. Conclusion: Chinese Herbal Medicine (CHM) offers a promising and safe treatment approach for patients dealing with Diarrheal Irritable Bowel Syndrome (IBS-D) accompanied by anxiety and depression; thus, indicating its potential for practical implementation. The most active metabolites of CHM could simultaneously act on the pathological targets of IBS-D, anxiety, and depression.The diverse scope of CHM's therapeutic role includes various aspects and objectives, underscoring its potential for broad utilization.

Research on high sensitivity piezoresistive sensor based on structural design.

With the popularity of smart terminals, wearable electronic devices have shown great market prospects, especially high-sensitivity pressure sensors, which can monitor micro-stimuli and high-precision dynamic external stimuli, and will have an important impact on future functional development. Compressible flexible sensors have attracted wide attention due to their simple sensing mechanism and the advantages of light weight and convenience. Sensors with high sensitivity are very sensitive to pressure and can detect resistance/current changes under pressure, which has been widely studied. On this basis, this review focuses on analyzing the performance impact of device structure design strategies on high sensitivity pressure sensors. The design of structures can be divided into interface microstructures and three-dimensional framework structures. The preparation methods of various structures are introduced in detail, and the current research status and future development challenges are summarized.

The Chinese keratoconus (CKC) cohort study.

The Chinese keratoconus (CKC) cohort study is a population-based longitudinal prospective cohort study in the Chinese population involving a clinical database and biobanks. This ongoing study focuses on the prevention of KC progression and is the first to involve the effect of gene‒environment interactions on KC progression. The CKC cohort is hospital-based and dynamic and was established in Zhengzhou, China; KC patients (n = 1114) from a large geographical area were enrolled from January 2019 to June 2023, with a mean age of 22.23 years (6‒57 years). Demographic details, socioeconomic characteristics, lifestyle, disease history, surgical history, family history, and visual and social function data are being collected using questionnaires. General physical examination, eye examination, biological specimen collection, and first-degree relative data were collected and analyzed in the present study. The primary focus of the present study was placed on gene, environment and the effect of gene‒environment interactions on KC progression. The follow-up of the CKC cohort study is expected to include data collection at 3 months, 6 months, and 1 year after the initial examination and then at the annual follow-up examinations. The first follow-up of the CKC cohort study was recorded. A total of 918 patients completed the follow-up by June 1, 2023, with a response rate of 82.40%. Aside from the younger age of patients who were followed up, no significant differences were found between patients who were followed up and patients who were not.

Associations of diet with infectious diseases in UK Biobank.

This research aims to utilize multivariate logistic regression to explore associations between the frequency of 13 food groups intake (or four diet groups) and infectious diseases. 487849 participants from the UK Biobank were enrolled, and 75209 participants were diagnosed with infectious diseases. Participants reporting the highest intake frequency of processed meat [odds ratio ( OR) = 1.0964; 95% CI: 1.0622-1.1318] and red meat ( OR = 1.0895; 95% CI: 1.0563-1.1239) had a higher risk of infectious diseases compared to those with the lowest intake frequency. Consuming fish 2.0-2.9 times ( OR = 0.8221; 95% CI: 0.7955-0.8496), cheese ≥5.0 times ( OR = 0.8822; 95% CI: 0.8559-0.9092), fruit 3.0-3.9 servings ( OR = 0.8867; 95% CI: 0.8661-0.9078), and vegetables 2.0-2.9 servings ( OR = 0.9372; 95% CI: 0.9189-0.9559) per week were associated with a lower risk of infection. Low meat-eaters ( OR = 0.9404; 95% CI: 0.9243-0.9567), fish-eaters ( OR = 0.8391; 95% CI: 0.7887-0.8919), and vegetarians ( OR = 0.9154; 95% CI: 0.8561-0.9778) had a lower risk of infectious diseases compared to regular meat-eaters. Mediation analysis was performed, revealing glycosylated hemoglobin, white blood cell counts, and body mass index were mediators in the relationships between diet groups and infectious diseases. This study suggested that intake frequency of food groups is a factor in infectious diseases and fish-eaters have a lower risk of infection.

Evaluating short-term and long-term liver fibrosis improvement in hepatitis C patients post-DAA treatment.

Despite achieving a high cure rate with direct-acting antivirals (DAAs) in hepatitis C treatment, further research is needed to identify additional benefits of the DAA therapy. The current study evaluated liver fibrosis improvement in 848 hepatitis C patients treated with DAAs, who also achieved sustained virologic response (SVR). Using the fibrosis-4 (FIB-4) index, patients were categorized based on their baseline fibrosis level, and improvements in fibrosis were analyzed in both the short-term (9-26 weeks) and long-term (≥ 36 weeks) follow-up. The results showed a significant decrease in the FIB-4 index, indicating an improvement in liver fibrosis, in 63.00% of the patients during the short-term follow-up and 67.56% during the long-term follow-up. Short-term improvement was associated with factors including ribavirin (RBV) usage, blood cholinesterase levels, alanine transaminase levels, albumin levels, and the baseline FIB-4 index. Additionally, long-term improvement was associated with factors such as aspartate transaminase levels, total protein level, and the baseline FIB-4 index. The current study emphasizes the importance of continuous assessment and post-treatment monitoring of liver fibrosis, providing crucial insights for enhancing patient care in hepatitis C management.

Deep Learning for Electromyographic Lower-Limb Motion Signal Classification Using Residual Learning.

Electromyographic (EMG) signals have gained popularity for controlling prostheses and exoskeletons, particularly in the field of upper limbs for stroke patients. However, there is a lack of research in the lower limb area, and standardized open-source datasets of lower limb EMG signals, especially recording data of Asian race features, are scarce. Additionally, deep learning algorithms are rarely used for human motion intention recognition based on EMG, especially in the lower limb area. In response to these gaps, we present an open-source benchmark dataset of lower limb EMG with Asian race characteristics and large data volume, the JJ dataset, which includes approximately 13,350 clean EMG segments of 10 gait phases from 15 people. This is the first dataset of its kind to include the nine main muscles of human gait when walking. We used the processed time-domain signal as input and adjusted ResNet-18 as the classification tool. Our research explores and compares multiple key issues in this area, including the comparison of sliding time window method and other preprocessing methods, comparison of time-domain and frequency-domain signal processing effects, cross-subject motion recognition accuracy, and the possibility of using thigh and calf muscles in amputees. Our experiments demonstrate that the adjusted ResNet can achieve significant classification accuracy, with an average accuracy rate of 95.34% for human gait phases. Our research provides a valuable resource for future studies in this area and demonstrates the potential for ResNet as a robust and effective method for lower limb human motion intention pattern recognition.

Leveraging Serial Low-Dose CT Scans in Radiomics-based Reinforcement Learning to Improve Early Diagnosis of Lung Cancer at Baseline Screening.

Purpose To evaluate the feasibility of leveraging serial low-dose CT (LDCT) scans to develop a radiomics-based reinforcement learning (RRL) model for improving early diagnosis of lung cancer at baseline screening. Materials and Methods In this retrospective study, 1951 participants (female patients, 822; median age, 61 years [range, 55-74 years]) (male patients, 1129; median age, 62 years [range, 55-74 years]) were randomly selected from the National Lung Screening Trial between August 2002 and April 2004. An RRL model using serial LDCT scans (S-RRL) was trained and validated using data from 1404 participants (372 with lung cancer) containing 2525 available serial LDCT scans up to 3 years. A baseline RRL (B-RRL) model was trained with only LDCT scans acquired at baseline screening for comparison. The 547 held-out individuals (150 with lung cancer) were used as an independent test set for performance evaluation. The area under the receiver operating characteristic curve (AUC) and the net reclassification index (NRI) were used to assess the performances of the models in the classification of screen-detected nodules. Results Deployment to the held-out baseline scans showed that the S-RRL model achieved a significantly higher test AUC (0.88 [95% CI: 0.85, 0.91]) than both the Brock model (AUC, 0.84 [95% CI: 0.81, 0.88]; P = .02) and the B-RRL model (AUC, 0.86 [95% CI: 0.83, 0.90]; P = .02). Lung cancer risk stratification was significantly improved by the S-RRL model as compared with Lung CT Screening Reporting and Data System (NRI, 0.29; P < .001) and the Brock model (NRI, 0.12; P = .008). Conclusion The S-RRL model demonstrated the potential to improve early diagnosis and risk stratification for lung cancer at baseline screening as compared with the B-RRL model and clinical models. Keywords: Radiomics-based Reinforcement Learning, Lung Cancer Screening, Low-Dose CT, Machine Learning © RSNA, 2024 Supplemental material is available for this article.

De novo transcriptome assembly database for 100 tissues from each of seven species of domestic herbivore.

Domesticated herbivores are an important agricultural resource that play a critical role in global food security, particularly as they can adapt to varied environments, including marginal lands. An understanding of the molecular basis of their biology would contribute to better management and sustainable production. Thus, we conducted transcriptome sequencing of 100 to 105 tissues from two females of each of seven species of herbivore (cattle, sheep, goats, sika deer, horses, donkeys, and rabbits) including two breeds of sheep. The quality of raw and trimmed reads was assessed in terms of base quality, GC content, duplication sequence rate, overrepresented k-mers, and quality score distribution with FastQC. The high-quality filtered RNA-seq raw reads were deposited in a public database which provides approximately 54 billion high-quality paired-end sequencing reads in total, with an average mapping rate of ~93.92%. Transcriptome databases represent valuable resources that can be used to study patterns of gene expression, and pathways that are related to key biological processes, including important economic traits in herbivores.

Identification of potential anti-tumor targets and mechanisms of HuaChanSu injection using network pharmacology and cytological experiments in Breast cancer.

HuaChanSu (HCS) or Cinobufacini injection is an aqueous extract of the dried skin of Bufo bufo gargarigans, and has anti-tumor effects. The aim of this study was to evaluate the possible therapeutic effect of HCS against breast cancer (BRCA) using cytology, network pharmacology, and molecular biology approaches. The half-inhibitory concentration (IC50) of HCS in the BRCA cells was determined by cytotoxicity assay, and were accordingly treated with high and low doses HCS in the TUNEL and scratch assays. The potential targets of HCS in the BRCA cells were identified through functional enrichment analysis and protein-protein interaction (PPI) networks, and verified by molecular docking. The expression levels of key signaling pathways-related proteins in HCS-treated BRCA cells by western blotting. HCS inhibited the proliferation and migration of MCF-7 and MDA-MB-231 cells, and induced apoptosis in a dose-dependent manner. Furthermore, we screened 289 core HCS targets against BRCA, which were primarily enriched in the PI3K-AKT, MAPK chemokines, and other. signaling pathways. In addition, PIK3CA, PIK3CD, and MTOR were confirmed as HCS targets by molecular docking. Consistent with this, we observed a reduction in the expression levels of phosphorylated PI3K, AKT, and MTOR in the HCS-treated BRCA cells. Taken together, our findings suggest that HCS inhibits the growth of BRCA cells by targeting the PI3K-AKT pathway, and warrants further investigation as a therapeutic agent for treating patients with BRCA.

Feeding Eucommia ulmoides extract enhances protection against high-temperature stress in chicks.

Chick's susceptibility to heat stress often leads to growth retardation, immune function impairment, disease, and mortality. This thesis explores the potential ameliorative effect of 0.8% Eucommia ulmoides extract (EUE) into the diet of heat-stressed chicks in a 15-d feeding trial. The investigation reveals that feeding EUE significantly enhances the BW, ADG, AFI, and F/G of chicks experiencing heat stress. Additionally, the EUE groups exhibited higher levels of T-AOC (at 7 and 15d), SOD (at 15 d), GSH-Px (at 15 d), as well as lower MDA concentrations (at 7 and 15d) in chick serum. Pathological changes and H&E staining revealed that EUE effectively improved tissue damage in the duodenum, heart, and stomach induced by heat stress in the chicks. The EUE groups also showed higher levels of IgA (at 7 d), IgG and IgM (at 7 and 15 d). RNA-seq and WGCNA analysis revealed that EUE mitigates cellular damage and losses in heat-stressed chicks primarily through pathways involving signal transduction, protein synthesis and degradation, as well as cell cycle regulation, particularly the latter. This investigation serves as a fundamental and cognitive framework for the development and application of Eucommia ulmoides feed additives aimed at safeguarding the well-being of chicks in adverse environmental conditions.

Value of Molecular Typing Combined with Integrated Positron Emission Tomography/Magnetic Resonance Imaging in Risk Stratification of Endometrial Cancer.

Objective: In this study, we investigated the value of molecular typing combined with integrated positron emission tomography (PET)/magnetic resonance imaging (MRI) semi-quantitative indices in endometrial cancer risk stratification. Methods: A retrospective study was conducted on 86 patients who were pathologically diagnosed with endometrial cancer and underwent surgical treatment after curettage at the Department of Obstetrics and Gynecology, Xuanwu Hospital, Capital Medical University between January 2017 and March 2023. Prior to surgery, each patient underwent integrated PET/MRI examination. The postoperative samples were subjected to pathological diagnosis, immunohistochemistry, and POLE gene sequencing. The differences in clinicopathological features between the four molecular subtypes and the differences in integrated PET/MRI semi-quantitative indexes (SUV max, ADC min) between the four molecular subtypes were analyzed. The cutoff value of molecular typing combined with integrated PET/MRI semi-quantitative indices for endometrial cancer risk stratification was determined. Results: There were statistically significant differences in pathological types and tumor grades among the four molecular subtypes of endometrial cancer. The values of the four integrated PET/MRI semi-quantitative indices (SUV max and ADC min) of the molecular subtypes were statistically different. The SUV max was greater in the p53abn mutation group than in the POLE mutation group (P < 0.05). The ADC minimum of the POLE mutation group and the MMR-d group was lower than the NSMP group (P < 0.05). Molecular typing combined with the integrated PET/MRI semi-quantitative SUV max index can predict the low/medium risk group of endometrial cancer and the medium-high/high risk group, and the cut-off value of SUV max for predicting the risk of early endometrial cancer was 14.72 (sensitivity 66.7%, specificity 68.7%). Conclusion: Molecular typing combined with integrated PET/MRI semi-quantitative indicators is useful to achieve risk stratification in patients diagnosed with endometrial cancer and guide individualized treatment.

Stomatal maturomics: hunting genes regulating guard cell maturation and function formation from single-cell transcriptomes.

Stomata play critical roles in gas exchange and immunity to pathogens. While many genes regulating early stomatal development up to the production of young guard cells (GCs) have been identified in Arabidopsis, much less is known about how young GCs develop into mature functional stomata. Here we perform a maturomics study on stomata, with "maturomics" defined as omics analysis of the maturation process of a tissue or organ. We develop an integrative scheme to analyze three public stomata-related single-cell RNA-seq datasets and identify a list of 586 genes that are specifically up-regulated in all three datasets during stomatal maturation and function formation. The list, termed sc_586, is enriched with known regulators of stomatal maturation and functions. To validate the reliability of the dataset, we selected two candidate G2-like transcription factor genes, MYS1 and MYS2, to investigate their roles in stomata. These two genes redundantly regulate the size and hoop rigidity of mature GCs, and the mys1 mys2 double mutatants cause mature GCs with severe defects in regulating their stomatal apertures. Taken together, our results provide a valuable list of genes for studying GC maturation and function formation.

New Insights into the Biological Functions of Essential TsaB/YeaZ Protein in Staphylococcus aureus.

TsaB/YeaZ represents a promising target for novel antibacterial agents due to its indispensable role in bacterial survival, high conservation within bacterial species, and absence of eukaryotic homologs. Previous studies have elucidated the role of the essential staphylococcal protein, TsaB/YeaZ, in binding DNA to mediate the transcription of the ilv-leu operon, responsible for encoding key enzymes involved in the biosynthesis of branched-chain amino acids-namely isoleucine, leucine, and valine (ILV). However, the regulation of ILV biosynthesis does not account for the essentiality of TsaB/YeaZ for bacterial growth. In this study, we investigated the impact of TsaB/YeaZ depletion on bacterial morphology and gene expression profiles using electron microscopy and deep transcriptomic analysis, respectively. Our results revealed significant alterations in bacterial size and surface smoothness upon TsaB/YeaZ depletion. Furthermore, we pinpointed specific genes and enriched biological pathways significantly affected by TsaB/YeaZ during the early and middle exponential phases and early stationary phases of growth. Crucially, our research uncovered a regulatory role for TsaB/YeaZ in bacterial autolysis. These discoveries offer fresh insights into the multifaceted biological functions of TsaB/YeaZ within S. aureus.

A Comparison of Currently Available and Investigational Fecal Microbiota Transplant Products for Recurrent Clostridioides difficile Infection.

Clostridioides difficile infection (CDI) is an intestinal infection that causes morbidity and mortality and places significant burden and cost on the healthcare system, especially in recurrent cases. Antibiotic overuse is well recognized as the leading cause of CDI in high-risk patients, and studies have demonstrated that even short-term antibiotic exposure can cause a large and persistent disturbance to human colonic microbiota. The recovery and sustainability of the gut microbiome after dysbiosis have been associated with fewer CDI recurrences. Fecal microbiota transplantation (FMT) refers to the procedure in which human donor stool is processed and transplanted to a patient with CDI. It has been historically used in patients with pseudomembranous colitis even before the discovery of Clostridioides difficile. More recent research supports the use of FMT as part of the standard therapy of recurrent CDI. This article will be an in-depth review of five microbiome therapeutic products that are either under investigation or currently commercially available: Rebyota (fecal microbiota, live-jslm, formerly RBX2660), Vowst (fecal microbiota spores, live-brpk, formerly SER109), VE303, CP101, and RBX7455. Included in this review is a comparison of the products' composition and dosage forms, available safety and efficacy data, and investigational status.

The Effect of Rhythmic Audio-Visual Stimulation on Inhibitory Control: An ERP Study.

Inhibitory control, as an essential cognitive ability, affects the development of higher cognitive functions. Rhythmic perceptual stimulation has been used to improve cognitive abilities. It is unclear, however, whether it can be used to improve inhibitory control. This study used the Go/NoGo task and the Stroop task to assess various levels of inhibitory control using rhythmic audio-visual stimuli as the stimulus mode. Sixty subjects were randomly divided into three groups to receive 6 Hz, 10 Hz, and white noise stimulation for 30 min. Two tasks were completed by each subject both before and after the stimulus. Before and after the task, closed-eye resting EEG data were collected. The results showed no differences in behavioral and EEG measures of the Go/NoGo task among the three groups. While both 6 Hz and 10 Hz audio-visual stimulation reduced the conflict effect in the Stroop task, only 6 Hz audio-visual stimulation improved the amplitude of the N2 component and decreased the conflict score. Although rhythmic audio-visual stimulation did not enhance response inhibition, it improved conflict inhibition.

Performance of a novel up-flow electrocatalytic hydrolysis acidification reactor (UEHAR) coupled with anoxic/oxic system for treating coking wastewater.

In this study, the performance of a novel up-flow electrocatalytic hydrolytic acidification reactor (UEHAR) and anoxic/oxic (ANO2/O2) combined system (S2) was compared with that of a traditional anaerobic/anoxic/oxic (ANA/ANO1/O1) system (S1) for treating coking wastewater at different hydraulic retention time (HRT). The effluent non-compliance rates of chemical oxygen demand (COD) of S2 were 45 %, 35 %, 25 % and 55 % lower than S1 with HRT of 94, 76, 65 and 54 h. The removal efficiency of benzene, toluene, ethylbenzene and xylene (BTEX) in S2 was 10.6 ± 2.4 % higher than that in S1. The effluent concentration of volatile phenolic compounds (VPs) in S2 was lower than 0.3 mg/L. The dehydrogenase activity (DHA) and adenosine triphosphate (ATP) of O2 were enhanced by 67.2 ± 26.3 % and 40.6 ± 14.2 % compared with O1, respectively. Moreover, COD was used to reflect the mineralization index of organic matter, and the positive correlation between COD removal rate and microbial activity, VPs, and BTEX was determined. These results indicated that S2 had extraordinary microbial activity, stable pollutant removal ability, and transcendental effluent compliance rate.

Reducing aerosol and ammonia emission in post-combustion CO2 capture: Additives as key solutions.

Advancement of the absorbent for CO2 capture is essential in optimizing the performance and reducing the negative environmental effects associated with this technology. Despite ammonia's promise as an absorbent, the volatility limits its practical application and creates potential environmental pollution. Therein, we assess various additives (amino acids, carbonates, and alkanolamines) for ammonia-based solvents using multi-stage circulation absorber from the viewpoints of aerosol emission, ammonia emission, and CO2 capture efficiency. Experimental findings reveal that ammonia volatilization can be inhibited by the protonation of free ammonia by carboxyl groups and the formation of hydrogen bonding between amino/hydroxyl groups and ammonia, with ammonia emission reduced by 21.7 %, aerosol emission reduced by 26.5 %, and CO2 capture efficiency increased to a maximum of 87.8 % under the condition of adding histidine. Moreover, the experiment highlights a positive correlation between total ammonia emission and aerosol concentration/diameter. Additionally, tests combining source abatement with water wash exhibit up to 50.5 % aerosol removal efficiency and up to 76.6 % ammonia removal efficiency. To further mitigate emissions, a comprehensive approach is proposed, achieving an 84.4 % reduction in ammonia emission and a 61.9 % reduction in aerosol emission. Finally, a method for recycling ammonia for desulfurization is suggested.

HiFi long-read amplicon sequencing for full-spectrum variants of human mtDNA.

BACKGROUND: Mitochondrial diseases (MDs) can be caused by single nucleotide variants (SNVs) and structural variants (SVs) in the mitochondrial genome (mtDNA). Presently, identifying deletions in small to medium-sized fragments and accurately detecting low-percentage variants remains challenging due to the limitations of next-generation sequencing (NGS). METHODS: In this study, we integrated targeted long-range polymerase chain reaction (LR-PCR) and PacBio HiFi sequencing to analyze 34 participants, including 28 patients and 6 controls. Of these, 17 samples were subjected to both targeted LR-PCR and to compare the mtDNA variant detection efficacy. RESULTS: Among the 28 patients tested by long-read sequencing (LRS), 2 patients were found positive for the m.3243 A > G hotspot variant, and 20 patients exhibited single or multiple deletion variants with a proportion exceeding 4%. Comparison between the results of LRS and NGS revealed that both methods exhibited similar efficacy in detecting SNVs exceeding 5%. However, LRS outperformed NGS in detecting SNVs with a ratio below 5%. As for SVs, LRS identified single or multiple deletions in 13 out of 17 cases, whereas NGS only detected single deletions in 8 cases. Furthermore, deletions identified by LRS were validated by Sanger sequencing and quantified in single muscle fibers using real-time PCR. Notably, LRS also effectively and accurately identified secondary mtDNA deletions in idiopathic inflammatory myopathies (IIMs). CONCLUSIONS: LRS outperforms NGS in detecting various types of SNVs and SVs in mtDNA, including those with low frequencies. Our research is a significant advancement in medical comprehension and will provide profound insights into genetics.