Machine learning in predicting T-score in the Oxford classification system of IgA nephropathy.

Background: Immunoglobulin A nephropathy (IgAN) is one of the leading causes of end-stage kidney disease (ESKD). Many studies have shown the significance of pathological manifestations in predicting the outcome of patients with IgAN, especially T-score of Oxford classification. Evaluating prognosis may be hampered in patients without renal biopsy. Methods: A baseline dataset of 690 patients with IgAN and an independent follow-up dataset of 1,168 patients were used as training and testing sets to develop the pathology T-score prediction (T pre) model based on the stacking algorithm, respectively. The 5-year ESKD prediction models using clinical variables (base model), clinical variables and real pathological T-score (base model plus T bio), and clinical variables and T pre (base model plus T pre) were developed separately in 1,168 patients with regular follow-up to evaluate whether T pre could assist in predicting ESKD. In addition, an external validation set consisting of 355 patients was used to evaluate the performance of the 5-year ESKD prediction model using T pre. Results: The features selected by AUCRF for the T pre model included age, systolic arterial pressure, diastolic arterial pressure, proteinuria, eGFR, serum IgA, and uric acid. The AUC of the T pre was 0.82 (95% CI: 0.80-0.85) in an independent testing set. For the 5-year ESKD prediction model, the AUC of the base model was 0.86 (95% CI: 0.75-0.97). When the T bio was added to the base model, there was an increase in AUC [from 0.86 (95% CI: 0.75-0.97) to 0.92 (95% CI: 0.85-0.98); P = 0.03]. There was no difference in AUC between the base model plus T pre and the base model plus T bio [0.90 (95% CI: 0.82-0.99) vs. 0.92 (95% CI: 0.85-0.98), P = 0.52]. The AUC of the 5-year ESKD prediction model using T pre was 0.93 (95% CI: 0.87-0.99) in the external validation set. Conclusion: A pathology T-score prediction (T pre) model using routine clinical characteristics was constructed, which could predict the pathological severity and assist clinicians to predict the prognosis of IgAN patients lacking kidney pathology scores.

Integration of artificial intelligence and multi-omics in kidney diseases.

Kidney disease is a leading cause of death worldwide. Currently, the diagnosis of kidney diseases and the grading of their severity are mainly based on clinical features, which do not reveal the underlying molecular pathways. More recent surge of ∼omics studies has greatly catalyzed disease research. The advent of artificial intelligence (AI) has opened the avenue for the efficient integration and interpretation of big datasets for discovering clinically actionable knowledge. This review discusses how AI and multi-omics can be applied and integrated, to offer opportunities to develop novel diagnostic and therapeutic means in kidney diseases. The combination of new technology and novel analysis pipelines can lead to breakthroughs in expanding our understanding of disease pathogenesis, shedding new light on biomarkers and disease classification, as well as providing possibilities of precise treatment.

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.

(+/-)-Dievodialetins A-G: Seven pairs of enantiomeric coumarin dimers with anti-acetylcholinesterase activity from the roots of Evodia lepta Merr.

Seven pairs of undescribed enantiomeric bis-coumarins, (±)-dievodialetins A-G, were separated from the roots of Evodia lepta Merr. Two coumarin nuclei were linked via a 1,4-dimethyl4-vinylcyclohexene moiety in (±)-dievodialetins C-G. The structures of the undescribed compounds, including their absolute configurations were elucidated by spectroscopic analyses, X-ray diffraction, and computational calculations. In the biosynthetic pathways, these bis-coumarins were presumably derived from the precursors demethylsuberosin and 3-(3-methylbut-2-enyl)umbelliferone via a [4 + 2] Diels-Alder reaction. Besides, all compounds exhibited neuroprotective effects by inhibiting acetylcholinesterase (AChE) activity with IC50 values ranging from 7.3 to 12.1 nM and they also suppressed oxidative stress (MDA and SOD) and neuroinflammation (IL-1ß and IL-6).

Polyphenols from the flower of Hibiscus syriacus Linn ameliorate neuroinflammation in LPS-treated SH-SY5Y cell.

The flower of Hibiscus syriacus Linn is a well-known traditional Chinese medicine (TCM) and health food in China, which has been used to treat dysentery, vaginal discharge, and hemorrhoids. In this study, five polyphenols (compounds 1-5) and five fatty acids (compounds 6-10) were isolated from the ethanol extract of the flower of H. syriacus. The isolated compounds were characterized by spectroscopic techniques. Polyphenols, an important type of natural product, have variety of biological activities. Here, we employed LPS or H2O2-treated SH-SY5Y cell models to test the neuroprotective effect of compounds 1-10. Results found compounds 1-5 (concentration range was around 20 µM on LPS model, concentration range was around 13 µM on H2O2 model), not compounds 6-10, exhibited neuroprotective effect in LPS or H2O2-treated SH-SY5Y cell. PCR analysis showed that compounds 1-5 can effectively improve the mRNA expression of synapse-related gene and neurotrophic factors (Syp, NGF and BDNF) in LPS-treated SH-SY5Y cell. In addition, compounds 1-5 decreased the levels of ROS and MDA and increased the activities of SOD, GSH-Px and CAT in LPS-treated SH-SY5Y cell. Furthermore, compounds 1-5 inhibited neuroinflammation (TNF-α, IL-1ß and IL-6) in LPS-treated SH-SY5Y cell. In conclusion, the polyphenols in the flower of H. syriacus could be a promising candidate for preventive effect of neuroinflammation.

Potential of herb-drug / herb interactions between substrates and inhibitors of UGTs derived from herbal medicines.

Herbal medicines are widely used as alternative or complementary therapies worldwide to treat and prevent chronic diseases. However, herbal medicines coadministration with therapeutic drugs may cause dramatic clinical herb-drug/herb interactions (HDIs/HHIs) that may result in low drug efficacy or serious toxic reactions. Phase II metabolism enzyme UDP-glucuronosyltransferases (UGTs) play a significant detoxification role in vivo. Most drugs and non-drug xenobiotics undergo phase II metabolic transformations to be more polar compounds that are more easily excreted. Herbal medicines are a mixed and chemically varied group that includes flavonoids, stilbenes, coumarins, quinones, and terpenes, which are potential substrates and inhibitors of UGTs. Although increasing studies about glucuronidation metabolism and the inhibition toward UGTs of many herbal medicines have been reported, it is still difficult to determine which compounds from herbal medicines are substrates or inhibitors of UGTs. This article gives an overview of UGTs studies, which mainly focuses on glucuronidation of herbal constituents as substrates catalyzed by UGTs, potential herbal inhibitors for UGTs. We summarize the negative effects of UGT1A polymorphism and single nucleotide polymorphisms (SNPs), relevant clinical situations of HDIs/HHIs induced by inhibition of UGTs, and propose establishing classification criteria for inhibitors. Finally, we also discuss future research and strategic directions to advance the understanding of the potential HDIs/HHIs and suggest some additional studies revealing more information on UGT-mediated HDIs/HHIs.

Colorimetric and fluorometric dual sensing of trace water in methanol based on a Schiff Base-Al3+ ensemble probe.

A new julolidine based Schiff base receptor (L) was synthesized and characterized. L forms a 1:1 complex with Al3+ in methanol, resulting in an immediate color change from chartreuse to orange and a remarkable enhancement in its emission intensity along with a bathochromic shift from 540 nm to 570 nm. Addition of trace amounts of water significantly quenches the fluorescence emission, where a decomplexation of Al3+ from the L-Al3+ complex takes place. The significant quenching effect indicated that the L-Al3+ ensemble system can be used to detect trace water in commercial methanol. From the fluorescence titration, the detection limit for sensing water in methanol was estimated to be 0.0047%. We have also made an easy-to-prepare test strip of L-Al3+ to detect water in methanol through naked-eye observation, which is possible to realize in situ monitoring.

[Metabolomics research of medicinal plants].

Metabolomics is the comprehensively study of chemical processes involving small molecule metabolites. It is an important part of systems biology, and is widely applied in complex traditional Chinese medicine（TCM）system. Metabolites biosynthesized by medicinal plants are the effective basis for TCM. Metabolomics studies of medicinal plants will usher in a new period of vigorous development with the implementation of Herb Genome Program and the development of TCM synthetic biology. This manuscript introduces the recent research progresses of metabolomics technology and the main research contents of metabolomics studies for medicinal plants, including identification and quality evaluation for medicinal plants, cultivars breeding, stress resistance, metabolic pathways, metabolic network, metabolic engineering and synthetic biology researches. The integration of genomics, transcriptomics and metabolomics approaches will finally lay foundation for breeding of medicinal plants, R&D, quality and safety evaluation of innovative drug.

Diagnostic accuracy of intracellular mycobacterium tuberculosis detection for tuberculous meningitis.

RATIONALE: Early diagnosis and treatment of tuberculous meningitis saves lives, but current laboratory diagnostic tests lack sensitivity. OBJECTIVES: We investigated whether the detection of intracellular bacteria by a modified Ziehl-Neelsen stain and early secretory antigen target (ESAT)-6 in cerebrospinal fluid leukocytes improves tuberculous meningitis diagnosis. METHODS: Cerebrospinal fluid specimens from patients with suspected tuberculous meningitis were stained by conventional Ziehl-Neelsen stain, a modified Ziehl-Neelsen stain involving cytospin slides with Triton processing, and an ESAT-6 immunocytochemical stain. Acid-fast bacteria and ESAT-6-expressing leukocytes were detected by microscopy. All tests were performed prospectively in a central laboratory by experienced technicians masked to the patients' final diagnosis. MEASUREMENTS AND MAIN RESULTS: Two hundred and eighty patients with suspected tuberculous meningitis were enrolled. Thirty-seven had Mycobacterium tuberculosis cultured from cerebrospinal fluid; 40 had a microbiologically confirmed alternative diagnosis; the rest had probable or possible tuberculous meningitis according to published criteria. Against a clinical diagnostic gold standard the sensitivity of conventional Ziehl-Neelsen stain was 3.3% (95% confidence interval, 1.6-6.7%), compared with 82.9% (95% confidence interval, 77.4-87.3%) for modified Ziehl-Neelsen stain and 75.1% (95% confidence interval, 68.8-80.6%) for ESAT-6 immunostain. Intracellular bacteria were seen in 87.8% of the slides positive by the modified Ziehl-Neelsen stain. The specificity of modified Ziehl-Neelsen and ESAT-6 stain was 85.0% (95% confidence interval, 69.4-93.8%) and 90.0% (95% confidence interval, 75.4-96.7%), respectively. CONCLUSIONS: Enhanced bacterial detection by simple modification of the Ziehl-Neelsen stain and an ESAT-6 intracellular stain improve the laboratory diagnosis of tuberculous meningitis.

Use of the metabolomics approach to characterize Chinese medicinal material Huangqi.

Integration of the genetic and metabolic fingerprinting can provide a new approach to differentiate similar Traditional Chinese Medical (TCM) materials. Two leguminous plants, Mojia Huangqi and Menggu Huangqi, are important medical herbs and share great similarities in morphology, chemical constituent, and genomic DNA sequence. The taxonomy of Mojia Huangqi and Menggu Huangqi has been debated for more than 50 years and discrimination of TCM materials directly affects the pharmacological and clinical effects. AFLP based genetic fingerprinting and GC-TOF/MS-based metabolic fingerprinting were used to successfully discriminate the two species. The results of AFLP supported the opinion that Menggu Huangqi was a variant of Mojia Huangqi. The metabolic fingerprinting showed growth locations have greater impacts on the metabolite composition and quantity than the genotypes (cultivated versus wild) in Menggu Huangqi. The difference of some soluble sugars, fatty acids, proline, and polyamine reflected plant adaptation to different growth environments. Using multivariate and univariate statistical analysis, three AFLP markers and eight metabolites were identified as candidate DNA and metabolic markers to distinguish the two herb materials. The correlation network between AFLP markers and metabolites revealed a complex correlation network, which indicated the special metabolic pathways and the regulation networks of Huangqi.

Sinapic acid derivatives from the seeds of Raphanus nussatirus L.

A new disulfide glycoside, raphthioglucoside (1), and a new sinapic acid derivative, sinapic acid 5-hydroxymethylfurfural ester (2), together with sinapic acid (3) have been isolated from the seeds of Raphanus nussatirus L. The structures of compounds 1-3 were determined based on chemical analysis and spectroscopic methods (UV, 1D and 2D NMR, HRFABMS, HREIMS and elemental analysis).