Developing A Baseline Metabolomic Signature Associated with COVID-19 Severity: Insights from Prospective Trials Encompassing 13 U.S. Centers.

Metabolic disease is a significant risk factor for severe COVID-19 infection, but the contributing pathways are not yet fully elucidated. Using data from two randomized controlled trials across 13 U.S. academic centers, our goal was to characterize metabolic features that predict severe COVID-19 and define a novel baseline metabolomic signature. Individuals (n = 133) were dichotomized as having mild or moderate/severe COVID-19 disease based on the WHO ordinal scale. Blood samples were analyzed using the Biocrates platform, providing 630 targeted metabolites for analysis. Resampling techniques and machine learning models were used to determine metabolomic features associated with severe disease. Ingenuity Pathway Analysis (IPA) was used for functional enrichment analysis. To aid in clinical decision making, we created baseline metabolomics signatures of low-correlated molecules. Multivariable logistic regression models were fit to associate these signatures with severe disease on training data. A three-metabolite signature, lysophosphatidylcholine a C17:0, dihydroceramide (d18:0/24:1), and triacylglyceride (20:4_36:4), resulted in the best discrimination performance with an average test AUROC of 0.978 and F1 score of 0.942. Pathways related to amino acids were significantly enriched from the IPA analyses, and the mitogen-activated protein kinase kinase 5 (MAP2K5) was differentially activated between groups. In conclusion, metabolites related to lipid metabolism efficiently discriminated between mild vs. moderate/severe disease. SDMA and GABA demonstrated the potential to discriminate between these two groups as well. The mitogen-activated protein kinase kinase 5 (MAP2K5) regulator is differentially activated between groups, suggesting further investigation as a potential therapeutic pathway.

Effect of single spinal anesthesia with two doses ropivacaine on urinary retention after hemorrhoidectomy in male patients.

Background: Anorectal diseases are common in the population and include internal, external, and mixed hemorrhoids. Although hemorrhoid surgery is a brief operation, anesthesia, anesthetic drugs, drug concentrations, and anesthesia level control are closely related to postoperative uroschesis. For hemorrhoid surgery, a single spinal block with ropivacaine is commonly used that blocks the S2-S4 parasympathetic nervous system, which in turn governs the voiding reflex, causing postoperative urinary retention; this affects the recovery of patients. This study was performed to investigate the effects of two doses ropivacaine that provided satisfactory analgesia and muscle relaxation and inhibited adverse reflexes on urinary retention after hemorrhoidectomy. Methods: The study included 200 male patients who underwent anorectal surgery with American Society of Anesthesiologists (ASA) grade I-II single elective spinal anesthesia between March 2021 and March 2022. Patients were randomly assigned to 2 groups using a random number table: Group A (n = 100) received 10 mg 0.5% ropivacaine (1.5 ml 1% ropivacaine + 1.5 ml 10% glucose = 3 ml), and Group B (n = 100) received 15 mg 0.5% ropivacaine (1.5 ml 1% ropivacaine + 1.5 ml 10% glucose = 3 ml). Results: The anal sphincter exhibited good relaxation, and no obvious traction pain or significant difference in the time of muscle strength recovery was observed between the 10 mg and 15 mg 0.5% ropivacaine groups (P > 0.05). The 10 mg 0.5% ropivacaine group had shorter time of micturition exceeding 100 ml and lower voiding International Prostate Symptom Score than the 15 mg 0.5% ropivacaine group (P < 0.01). Conclusions: Single spinal anesthesia with 10 mg 0.5% ropivacaine not only provides satisfactory anesthetic effect for hemorrhoidectomy but also has less influence on postoperative uroschesis and is worthy of clinical application. Trial registration: The study was registered in the Chinese Clinical Trial Registry (http://www.chictr.org.cn; identifier: ChiCTR2,100,043,686) on February 27, 2021.

Sleep Quality Evaluation Based on Single-Lead Wearable Cardiac Cycle Acquisition Device.

In clinical conditions, polysomnography (PSG) is regarded as the "golden standard" for detecting sleep disease and offering a reference of objective sleep quality. For healthy adults, scores from sleep questionnaires are more reliable than other methods in obtaining knowledge of subjective sleep quality. In practice, the need to simplify PSG to obtain subjective sleep quality by recording a few channels of physiological signals such as single-lead electrocardiogram (ECG) or photoplethysmography (PPG) signal is still very urgent. This study provided a two-step method to differentiate sleep quality into "good sleep" and "poor sleep" based on the single-lead wearable cardiac cycle data, with the comparison of the subjective sleep questionnaire score. First, heart rate variability (HRV) features and ECG-derived respiration features were extracted to construct a sleep staging model (wakefulness (W), rapid eye movement (REM), light sleep (N1&N2) and deep sleep (N3)) using the multi-classifier fusion method. Then, features extracted from the sleep staging results were used to construct a sleep quality evaluation model, i.e., classifying the sleep quality as good and poor. The accuracy of the sleep staging model, tested on the international public database, was 0.661 and 0.659 in Cardiology Challenge 2018 training database and Sleep Heart Health Study Visit 1 database, respectively. The accuracy of the sleep quality evaluation model was 0.786 for our recording subjects, with an average F1-score of 0.771. The proposed sleep staging model and sleep quality evaluation model only requires one channel of wearable cardiac cycle signal. It is very easy to transplant to portable devices, which facilitates daily sleep health monitoring.

Comparative metabolomic profiling in the roots and leaves in contrasting genotypes reveals complex mechanisms involved in post-anthesis drought tolerance in wheat.

Understanding the contrasting biochemical changes in different plant parts in response to drought can help to formulate smart strategies to develop drought tolerant genotypes. The current study used metabolomics and physiological approaches to understand the differential biochemical changes coupled with physiological adjustments in leaves and roots to cope with drought stress in two wheat genotypes, LA754 (drought tolerant) and AGS2038 (drought sensitive). The gas chromatography-mass spectrometry (GC-MS) analysis and physiological trait estimation were performed in the roots and leaves after drought imposition. Drought induced reduction was observed in all physiological and yield related traits. In LA754, higher numbers of metabolites were altered in leaves (45) compared to roots (20) which indicates that plants allocated more resources to leaves in tolerant genotype. In addition, the metabolic components of the root were less affected by the stress which supports the idea that the roots are more drought tolerant than the leaf or shoot. In AGS2038, thirty and twenty eight metabolites were altered in the leaves and roots, respectively. This indicates that the sensitive genotype compromised resource allocation to leaves, rather allocated more towards roots. Tryptophan, valine, citric acid, fumaric acid, and malic acid showed higher accumulation in leaf in LA754, but decreased in the root, while glyceric acid was highly accumulated in the root, but not in the leaf. The results demonstrated that the roots and shoots have a different metabolic composition, and shoot metabolome is more variable than the root metabolome. Though the present study demonstrated that the metabolic response of shoots to drought contrasts with that of roots, some growth metabolites (protein, sugar, etc) showed a mirror increase in both parts. Protein synthesis and energy cycle was active in both organs, and the organs were metabolically activated to enhance water uptake and maintain growth to mitigate the effect of drought.

Comparative Physiological and Metabolic Analysis Reveals a Complex Mechanism Involved in Drought Tolerance in Chickpea (Cicer arietinum L.) Induced by PGPR and PGRs.

The plant growth promoting rhizobacteria (PGPR) and plant growth regulators (PGRs) can be applied to improve the growth and productivity of plants, with potential to be used for genetic improvement of drought tolerance. However, for genetic improvement to be achieved, a solid understanding of the physiological and biochemical changes in plants induced by PGPR and PGR is required. The present study was carried out to investigate the role of PGPR and PGRs on the physiology and biochemical changes in chickpea grown under drought stress conditions and their association with drought tolerance. The PGPR, isolated from the rhizosphere of chickpea, were characterized on the basis of colony morphology and biochemical characters. They were also screened for the production of indole-3-acetic acid (IAA), hydrogen cyanide (HCN), ammonia (NH3), and exopolysaccharides (EPS) production. The isolated PGPR strains, named P1, P2, and P3, were identified by 16S-rRNA gene sequencing as Bacillus subtilis, Bacillus thuringiensis, and Bacillus megaterium, respectively. The seeds of two chickpea varieties, Punjab Noor-2009 (drought sensitive) and 93127 (drought tolerant) were soaked for 2-3 h prior to sowing in 24 h old cultures of isolates. The salicylic acid (SA) and putrescine (Put) were sprayed (150 mg/L) on 25 day old chickpea seedlings. The results showed that chickpea plants treated with a consortium of PGPR and PGRs significantly enhanced the chlorophyll, protein, and sugar contents compared to irrigated and drought conditions. Leaf proline content, lipid peroxidation, and activities of antioxidant enzymes (CAT, APOX, POD, and SOD) all increased in response to drought stress but decreased due to the PGPR and PGRs treatment. An ultrahigh performance liquid chromatography-high resolution mass spectrometry (UPLC-HRMS) analysis was carried out for metabolic profiling of chickpea leaves planted under controlled (well-irrigated), drought, and consortium (drought plus PGPR and PGRs) conditions. Proline, L-arginine, L-histidine, L-isoleucine, and tryptophan were accumulated in the leaves of chickpea exposed to drought stress. Consortium of PGPR and PGRs induced significant accumulation of riboflavin, L-asparagine, aspartate, glycerol, nicotinamide, and 3-hydroxy-3-methyglutarate in the leaves of chickpea. The drought sensitive chickpea variety showed significant accumulation of nicotinamide and 4-hydroxy-methylglycine in PGPR and PGR treated plants at both time points (44 and 60 days) as compared to non-inoculated drought plants. Additionally, arginine accumulation was also enhanced in the leaves of the sensitive variety under drought conditions. Metabolic changes as a result of drought and consortium conditions highlighted pools of metabolites that affect the metabolic and physiological adjustments in chickpea that reduce drought impacts.