Evaluating the efficacy and safety of perianal injection of liposomal ropivacaine HR18034 for postoperative analgesia following hemorrhoidectomy: A multicenter, randomized, double-blind, controlled phase II clinical trial.

STUDY OBJECTIVE: HR18034, composed of the ropivacaine encapsulated in multi-lamellar, concentric circular structure liposomes as the major component and a small amount of free ropivacaine, has performed well in animal experiments and phase I clinical trials. This trial was to investigate the efficacy, safety, pharmacokinetic profile and the minimum effective dose of HR18034 for postoperative analgesia after hemorrhoidectomy compared with ropivacaine. DESIGN: A multicenter, randomized, double-blind trial. SETTING: 19 medical centers in China. PATIENTS: 85 patients undergoing hemorrhoidectomy between October 2022 to November 2022. INTERVENTIONS: Patients were randomly divided into HR 18034 190 mg group, 285 mg group, 380 mg group and ropivacaine 75 mg group, receiving single local anesthetic perianal injection for postoperative analgesia. MEASUREMENTS: The primary outcome was the area under the resting state NRS score -time curve within 72 h after injection. The second outcomes included the proportion of patients without pain, the proportion of patients not requiring rescue analgesia, cumulative morphine consumption for rescue analgesia, etc. Safety was evaluated by adverse events incidence and plasma ropivacaine concentrations were measured to explore the pharmacokinetic characteristics of HR18034. MAIN RESULTS: The areas under the NRS score (at rest and moving states)-time curve were significantly lower in HR 18034 380 mg group than ropivacaine 75 mg at 24 h, 48 h, and 72 h after administration. However, this superiority was not observed in HR18034 190 mg group and 285 mg group. There was no difference in cumulative morphine consumption for rescue analgesia between HR 18034 groups and ropivacaine group. CONCLUSIONS: HR 18034 380 mg showed superior analgesic efficacy and equivalent safety compared to ropivacaine 75 mg after hemorrhoidectomy, thus preliminarily determined as minimum effective dose.

A two-step method of cyclolinopeptide (linusorb) preparation from flaxseed cake via dry-screening.

Linusorbs (LO), cyclolinopeptides, are a group of cyclic hydrophobic peptides and considered a valuable by-product of flaxseed oil due to numerous health benefits. Currently applied acetone or methanol extraction could contaminate the feedstocks for further food-grade application. Using flaxseed cake as feedstock, this study established a practical method for preparing LO from pressed cake. Firstly, LO composition of 15 flaxseed cultivars was analyzed. Next, cold-pressed cake was milled and screened mechanically. The kernel and hull fractions were separated based on the disparity of their mechanical strength. Monitored by hyperspectral fluorescence, the LO-enriched kernel fraction separated from cold-pressed flaxseed cake was further used as feedstock for LO production. After ethanol extraction, partition, and precipitation, LOs were extracted from cold-pressed flaxseed cake with a purity of 91.4%. The proposed method could serve as feasible flaxseed cake valorization strategy and enable the preparation of other polar compounds such as flax lignan and mucilage.

From gut to liver: unveiling the differences of intestinal microbiota in NAFL and NASH patients.

Non-alcoholic fatty liver disease (NAFLD) is increasingly recognized for its global prevalence and potential progression to more severe liver diseases such as non-alcoholic steatohepatitis (NASH). The gut microbiota plays a pivotal role in the pathogenesis of NAFLD, yet the detailed characteristics and ecological alterations of gut microbial communities during the progression from non-alcoholic fatty liver (NAFL) to NASH remain poorly understood. Methods: In this study, we conducted a comparative analysis of gut microbiota composition in individuals with NAFL and NASH to elucidate differences and characteristics. We utilized 16S rRNA sequencing to compare the intestinal gut microbiota among a healthy control group (65 cases), NAFL group (64 cases), and NASH group (53 cases). Random forest machine learning and database validation methods were employed to analyze the data. Results: Our findings indicate a significant decrease in the diversity of intestinal flora during the progression of NAFLD (p < 0.05). At the phylum level, high abundances of Bacteroidetes and Fusobacteria were observed in both NAFL and NASH patients, whereas Firmicutes were less abundant. At the genus level, a significant decrease in Prevotella expression was seen in the NAFL group (AUC 0.738), whereas an increase in the combination of Megamonas and Fusobacterium was noted in the NASH group (AUC 0.769). Furthermore, KEGG pathway analysis highlighted significant disturbances in various types of glucose metabolism pathways in the NASH group compared to the NAFL group, as well as notably compromised flavonoid and flavonol biosynthesis functions. The study uncovers distinct microbiota characteristics and microecological changes within the gut during the transition from NAFL to NASH, providing insights that could facilitate the discovery of novel biomarkers and therapeutic targets for NAFLD.

Differential diagnosis of Crohn's disease and intestinal tuberculosis based on ATR-FTIR spectroscopy combined with machine learning.

BACKGROUND: Crohn's disease (CD) is often misdiagnosed as intestinal tuberculosis (ITB). However, the treatment and prognosis of these two diseases are dramatically different. Therefore, it is important to develop a method to identify CD and ITB with high accuracy, specificity, and speed. AIM: To develop a method to identify CD and ITB with high accuracy, specificity, and speed. METHODS: A total of 72 paraffin wax-embedded tissue sections were pathologically and clinically diagnosed as CD or ITB. Paraffin wax-embedded tissue sections were attached to a metal coating and measured using attenuated total reflectance fourier transform infrared spectroscopy at mid-infrared wavelengths combined with XGBoost for differential diagnosis. RESULTS: The results showed that the paraffin wax-embedded specimens of CD and ITB were significantly different in their spectral signals at 1074 cm-1 and 1234 cm-1 bands, and the differential diagnosis model based on spectral characteristics combined with machine learning showed accuracy, specificity, and sensitivity of 91.84%, 92.59%, and 90.90%, respectively, for the differential diagnosis of CD and ITB. CONCLUSION: Information on the mid-infrared region can reveal the different histological components of CD and ITB at the molecular level, and spectral analysis combined with machine learning to establish a diagnostic model is expected to become a new method for the differential diagnosis of CD and ITB.

Evaluation standards regulate the generation and selection of novel ideas in creative behaviors: insights from individual differences in event-related potentials.

Evaluation is generally considered to occur after the generation of novel ideas to select truly creative ideas; however, evaluation may occur concurrently with the generation and regulate its efficiency. To test this hypothesis, 120 participants who held strict, moderate, or loose evaluation standards were grouped, and neural responses related to novel idea generation were compared retrospectively. The results showed that lower N400 amplitudes and greater LSP amplitudes were simultaneously elicited by objectively defined novel and usable options than by novel but unusable options among participants with moderate standards but not among participants with strict or loose standards. Evaluation standards influence the efficiency of novel idea generation; neither strict nor loose evaluation standards are conducive to fully resolving cognitive conflicts and generating novel ideas. Moreover, lower N400 amplitudes and greater LSP amplitudes were simultaneously elicited by the subjectively rated novel and usable option than by the novel but unusable option among participants with strict and moderate standards but not among participants with loose standards. Evaluation standards influence the selection among the generated ideas; participants in the strict and moderate groups made a wise choice based on the degree of conflict resolution, whereas participants in the loose group did not.

A survey of recent methods for addressing AI fairness and bias in biomedicine.

OBJECTIVES: Artificial intelligence (AI) systems have the potential to revolutionize clinical practices, including improving diagnostic accuracy and surgical decision-making, while also reducing costs and manpower. However, it is important to recognize that these systems may perpetuate social inequities or demonstrate biases, such as those based on race or gender. Such biases can occur before, during, or after the development of AI models, making it critical to understand and address potential biases to enable the accurate and reliable application of AI models in clinical settings. To mitigate bias concerns during model development, we surveyed recent publications on different debiasing methods in the fields of biomedical natural language processing (NLP) or computer vision (CV). Then we discussed the methods, such as data perturbation and adversarial learning, that have been applied in the biomedical domain to address bias. METHODS: We performed our literature search on PubMed, ACM digital library, and IEEE Xplore of relevant articles published between January 2018 and December 2023 using multiple combinations of keywords. We then filtered the result of 10,041 articles automatically with loose constraints, and manually inspected the abstracts of the remaining 890 articles to identify the 55 articles included in this review. Additional articles in the references are also included in this review. We discuss each method and compare its strengths and weaknesses. Finally, we review other potential methods from the general domain that could be applied to biomedicine to address bias and improve fairness. RESULTS: The bias of AIs in biomedicine can originate from multiple sources such as insufficient data, sampling bias and the use of health-irrelevant features or race-adjusted algorithms. Existing debiasing methods that focus on algorithms can be categorized into distributional or algorithmic. Distributional methods include data augmentation, data perturbation, data reweighting methods, and federated learning. Algorithmic approaches include unsupervised representation learning, adversarial learning, disentangled representation learning, loss-based methods and causality-based methods.

Gut microbiota-derived gamma-aminobutyric acid from metformin treatment reduces hepatic ischemia/reperfusion injury through inhibiting ferroptosis.

Hepatic ischemia/reperfusion injury (HIRI) is a common and inevitable factor leading to poor prognosis in various liver diseases, making the outcomes of current treatments in clinic unsatisfactory. Metformin has been demonstrated to be beneficial to alleviate HIRI in recent studies, however, the underpinning mechanism remains unclear. In this study, we found metformin mitigates HIRI-induced ferroptosis through reshaped gut microbiota in mice, which was confirmed by the results of fecal microbiota transplantation treatment but showed the elimination of the beneficial effects when gut bacteria were depleted using antibiotics. Detailedly, through 16S rRNA and metagenomic sequencing, we identified that the metformin-reshaped microbiota was characterized by the increase of gamma-aminobutyric acid (GABA) producing bacteria. This increase was further confirmed by the elevation of GABA synthesis key enzymes, glutamic acid decarboxylase and putrescine aminotransferase, in gut microbes of metformin-treated mice and healthy volunteers. Furthermore, the benefit of GABA against HIRI-induced ferroptosis was demonstrated in GABA-treated mice. Collectively, our data indicate that metformin can mitigate HIRI-induced ferroptosis by reshaped gut microbiota, with GABA identified as a key metabolite.

A survey of recent methods for addressing AI fairness and bias in biomedicine.

Objectives: Artificial intelligence (AI) systems have the potential to revolutionize clinical practices, including improving diagnostic accuracy and surgical decision-making, while also reducing costs and manpower. However, it is important to recognize that these systems may perpetuate social inequities or demonstrate biases, such as those based on race or gender. Such biases can occur before, during, or after the development of AI models, making it critical to understand and address potential biases to enable the accurate and reliable application of AI models in clinical settings. To mitigate bias concerns during model development, we surveyed recent publications on different debiasing methods in the fields of biomedical natural language processing (NLP) or computer vision (CV). Then we discussed the methods, such as data perturbation and adversarial learning, that have been applied in the biomedical domain to address bias. Methods: We performed our literature search on PubMed, ACM digital library, and IEEE Xplore of relevant articles published between January 2018 and December 2023 using multiple combinations of keywords. We then filtered the result of 10,041 articles automatically with loose constraints, and manually inspected the abstracts of the remaining 890 articles to identify the 55 articles included in this review. Additional articles in the references are also included in this review. We discuss each method and compare its strengths and weaknesses. Finally, we review other potential methods from the general domain that could be applied to biomedicine to address bias and improve fairness. Results: The bias of AIs in biomedicine can originate from multiple sources such as insufficient data, sampling bias and the use of health-irrelevant features or race-adjusted algorithms. Existing debiasing methods that focus on algorithms can be categorized into distributional or algorithmic. Distributional methods include data augmentation, data perturbation, data reweighting methods, and federated learning. Algorithmic approaches include unsupervised representation learning, adversarial learning, disentangled representation learning, loss-based methods and causality-based methods.

The impact of social distancing measures on anti-JC virus serostatus changes before and during the COVID-19 pandemic in US patients with multiple sclerosis.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic offered an epidemiological opportunity to evaluate if isolation and masking affected John Cunningham (JC) virus transmission. OBJECTIVE: This study aimed to assess the proportion of natalizumab-treated patients who converted to a positive anti-JCV antibody serostatus before and during the pandemic. METHODS: Data from TYSABRI Outreach: Unified Commitment to Health (TOUCH) for 22,375 US patients treated with natalizumab with anti-JCV antibody records were assessed in epochs annually from 2017 to 2022. RESULTS: Pre-pandemic anti-JCV antibody serostatus change was observed for 7.4%-7.7%. During the first and second years of the pandemic, 7.3% and 7.2% of patients' serostatus changed, respectively. CONCLUSION: The proportion of patients with anti-JCV antibody serostatus change did not significantly differ during the first 2 years of the pandemic compared with prior years. In contrast to seasonal influenza, masking and social distancing had no discernable effect on JCV serostatus change.

Unmasking and Quantifying Racial Bias of Large Language Models in Medical Report Generation.

Large language models like GPT-3.5-turbo and GPT-4 hold promise for healthcare professionals, but they may inadvertently inherit biases during their training, potentially affecting their utility in medical applications. Despite few attempts in the past, the precise impact and extent of these biases remain uncertain. Through both qualitative and quantitative analyses, we find that these models tend to project higher costs and longer hospitalizations for White populations and exhibit optimistic views in challenging medical scenarios with much higher survival rates. These biases, which mirror real-world healthcare disparities, are evident in the generation of patient backgrounds, the association of specific diseases with certain races, and disparities in treatment recommendations, etc. Our findings underscore the critical need for future research to address and mitigate biases in language models, especially in critical healthcare applications, to ensure fair and accurate outcomes for all patients.

Divergent thinking benefits from functional antagonism of the left IFG and right TPJ: a transcranial direct current stimulation study.

Divergent thinking is assumed to benefit from releasing the constraint of existing knowledge (i.e. top-down control) and enriching free association (i.e. bottom-up processing). However, whether functional antagonism between top-down control-related and bottom-up processing-related brain structures is conducive to generating original ideas is largely unknown. This study was designed to investigate the effect of functional antagonism between the left inferior frontal gyrus and the right temporoparietal junction on divergent thinking performance. A within-subjects design was adopted for three experiments. A total of 114 participants performed divergent thinking tasks after receiving transcranial direct current stimulation over target regions. In particular, cathodal stimulation over the left inferior frontal gyrus and anodal stimulation over the right inferior frontal gyrus (Experiment 1), anodal stimulation over the right temporoparietal junction (Experiment 2), and both cathodal stimulation over the left inferior frontal gyrus and anodal stimulation over the right temporoparietal junction (Experiment 3) were manipulated. Compared with sham stimulation, the combination of hyperpolarization of the left inferior frontal gyrus and depolarization of the right temporoparietal junction comprehensively promoted the fluency, flexibility, and originality of divergent thinking without decreasing the rationality of generated ideas. Functional antagonism between the left inferior frontal gyrus (hyperpolarization) and right temporoparietal junction (depolarization) has a "1 + 1 > 2" superposition effect on divergent thinking.

Prevotella histicola Prevented Particle-Induced Osteolysis via Gut Microbiota-Dependent Modulation of Inflammation in Ti-Treated Mice.

Wear particles generated from total joint replacements induce chronic osteolysis mediated by inflammatory upregulation, which leads to implant failure. Recent studies have suggested an important role of the gut microbiota in modulating the host's metabolism and immune system, leading to alterations in bone mass. Following gavage with P. histicola, micro-CT and HE staining revealed that osteolysis was significantly reduced in titanium (Ti)-treated mice. Immunofluorescence analysis revealed an increased macrophage (M)1/M2 ratio in the guts of Ti-treated mice, which decreased when P. histicola was added. P. histicola was also found to upregulate the tight junction proteins ZO-1, occludin, claudin-1, and MUC2 in the gut, reduce the levels of inflammatory factors IL-1ß, IL-6, IL-8, and TNF-α, primarily in the ileum and colon, and decrease the expression of IL-1ß and TNF-α and increase the level of IL-10 in the serum and cranium. Furthermore, P. histicola treatment resulted in a significant downregulation of CTX-1, RANKL, and RANKL/OPG. These findings demonstrate that P. histicola significantly mitigates osteolysis in Ti-treated mice by improving intestinal microbiota that repairs intestinal leakage and reduces systemic and local inflammation which in turn inhibits RANKL expression for bone resorption. P. histicola treatment may thus be therapeutically beneficial for particle-induced osteolysis.

Androgen Receptor/AP-1 Activates UGT2B15 Transcription to Promote Esophageal Squamous Cell Carcinoma Invasion.

Esophageal squamous cell carcinoma (ESCC) is an aggressive epithelial malignancy with poor prognosis. Interestingly, ESCC is strongly characterized by a male-predominant propensity. Our previous study showed that androgen receptor (AR) orchestrated a transcriptional repression program to promote ESCC growth, but it remains unclear whether AR can also activate oncogenic signaling during ESCC progression. In this study, by analyzing our previous AR cistromes and androgen-regulated transcriptomes, we identified uridine diphosphate glucuronosyltransferase family 2 member B15 (UGT2B15) as a bona fide target gene of AR. Mechanistically, AP-1 cofactors played important and collaborative roles in AR-mediated UGT2B15 upregulation. Functional studies have revealed that UGT2B15 promoted invasiveness in vitro and lymph node metastasis in vivo. UGT2B15 was partially responsible for the AR-induced invasive phenotype in ESCC cells. Importantly, simultaneous blocking of AP-1 and AR resulted in stronger inhibition of cell invasiveness compared to inhibiting AP-1 or AR alone. In conclusion, our study reveals the molecular mechanisms underlying the AR-driven ESCC invasion and suggests that the AR/AP1/UGT2B15 transcriptional axis can be potentially targeted in suppressing metastasis in male ESCC patients.

A classical herbal formula alleviates high-fat diet induced nonalcoholic steatohepatitis (NASH) via targeting mitophagy to rehabilitate dysfunctional mitochondria, validated by UPLC-HRMS identification combined with in vivo experiment.

BACKGROUND: Nonalcoholic steatohepatitis (NASH) has caused a significant burden on public health care systems, the economy and society. However, there has still been no officially approved pharmacotherapy for NASH. It has been suggested that oxidative stress and mitochondrial dysfunction play vital roles in NASH pathological progression. Shugan Xiaozhi (SG) formula, as a kind of classical herbal formula, was shown to attenuate NASH. PURPOSE: This study aimed to explore the potential mechanisms of SG formula treating NASH. STUDY DESIGN AND METHODS: Ultra-high-performance liquid chromatography-high resolution mass spectrometry combined with bioinformatics analysis was applied to explore the therapeutic targets and main components of SG formula. Moreover, in vivo NASH model was utilized to confirmed the therapeutic effects of SG formula. Molecular docking analysis and further validation experiments were conducted to verify the results of bioinformatics analysis. RESULTS: The in vivo experiments confirmed SG formula significantly attenuated hepatic pathological progression and relieved oxidative stress in high-fat diet (HFD) induced - NASH model. Ultra-high-performance liquid chromatography-high resolution mass spectrometry (UPLC-HRMS) combined with bioinformatics analysis expounded the components of SG formula and revealed the mitochondrial regulation mechanism of SG formula treating NASH. Further in vivo experiments validated that SG formula could alleviate oxidative stress by rehabilitating the structure and function of mitochondria, which was strongly related to regulating mitophagy. CONCLUSION: In summary, this study demonstrated that SG formula, which could attenuate NASH by regulating mitochondria and might be a potential pharmacotherapy for NASH.

Application for Identifying the Origin and Predicting the Physiologically Active Ingredient Contents of Gastrodia elata Blume Using Visible-Near-Infrared Spectroscopy Combined with Machine Learning.

Gastrodia elata (G. elata) Blume is widely used as a health product with significant economic, medicinal, and ecological values. Due to variations in the geographical origin, soil pH, and content of organic matter, the levels of physiologically active ingredient contents in G. elata from different origins may vary. Therefore, rapid methods for predicting the geographical origin and the contents of these ingredients are important for the market. This paper proposes a visible-near-infrared (Vis-NIR) spectroscopy technology combined with machine learning. A variety of machine learning models were benchmarked against a one-dimensional convolutional neural network (1D-CNN) in terms of accuracy. In the origin identification models, the 1D-CNN demonstrated excellent performance, with the F1 score being 1.0000, correctly identifying the 11 origins. In the quantitative models, the 1D-CNN outperformed the other three algorithms. For the prediction set of eight physiologically active ingredients, namely, GA, HA, PE, PB, PC, PA, GA + HA, and total, the RMSEP values were 0.2881, 0.0871, 0.3387, 0.2485, 0.0761, 0.7027, 0.3664, and 1.2965, respectively. The Rp2 values were 0.9278, 0.9321, 0.9433, 0.9094, 0.9454, 0.9282, 0.9173, and 0.9323, respectively. This study demonstrated that the 1D-CNN showed highly accurate non-linear descriptive capability. The proposed combinations of Vis-NIR spectroscopy with 1D-CNN models have significant potential in the quality evaluation of G. elata.

The Role of Retinal Dopamine D1 Receptors in Ocular Growth and Myopia Development in Mice.

Dopamine is a key neurotransmitter in the signaling cascade controlling ocular refractive development, but the exact role and site of action of dopamine D1 receptors (D1Rs) involved in myopia remains unclear. Here, we determine whether retinal D1Rs exclusively mediate the effects of endogenous dopamine and systemically delivered D1R agonist or antagonist in the mouse form deprivation myopia (FDM) model. Male C57BL/6 mice subjected to unilateral FDM or unobstructed vision were divided into the following four groups: one noninjected and three groups that received intraperitoneal injections of a vehicle, D1R agonist SKF38393 (18 and 59 nmol/g), or D1R antagonist SCH39166 (0.1 and 1 nmol/g). The effects of these drugs on FDM were further assessed in Drd1-knock-out (Drd1-KO), retina-specific conditional Drd1-KO (Drd1-CKO) mice, and corresponding wild-type littermates. In the visually unobstructed group, neither SKF38393 nor SCH39166 affected normal refractive development, whereas myopia development was attenuated by SKF38393 and enhanced by SCH39166 injections. In Drd1-KO or Drd1-CKO mice, however, these drugs had no effect on FDM development, suggesting that activation of retinal D1Rs is pertinent to myopia suppression by the D1R agonist. Interestingly, the development of myopia was unchanged by either Drd1-KO or Drd1-CKO, and neither SKF38393 nor SCH39166 injections, nor Drd1-KO, affected the retinal or vitreal dopamine and the dopamine metabolite DOPAC levels. Effects on axial length were less marked than effects on refraction. Therefore, activation of D1Rs, specifically retinal D1Rs, inhibits myopia development in mice. These results also suggest that multiple dopamine D1R mechanisms play roles in emmetropization and myopia development.SIGNIFICANCE STATEMENT While dopamine is recognized as a "stop" signal that inhibits myopia development (myopization), the location of the dopamine D1 receptors (D1Rs) that mediate this action remains to be addressed. Answers to this key question are critical for understanding how dopaminergic systems regulate ocular growth and refraction. We report here the results of our study showing that D1Rs are essential for controlling ocular growth and myopia development in mice, and for identifying the retina as the site of action for dopaminergic control via D1Rs. These findings highlight the importance of intrinsic retinal dopaminergic mechanisms for the regulation of ocular growth and suggest specific avenues for exploring the retinal mechanisms involved in the dopaminergic control of emmetropization and myopization.

Case report: A rare multidrug-resistant Escherichia coli causes fatal neonatal meningoencephalitis.

Neonatal meningitis is rare but devastating disease. Multidrug-resistant (MDR, multi-drug resistant) bacteria are a major global health risk. We report an Escherichia coli meningitis isolate with multiple resistance patterns and unusual serotype (O75) that caused sudden neonatal death. The isolate was resistant to antibiotics other than cefoperazone/sulbactam and imipenem, challenging the combination of antibiotics commonly used in the empirical treatment of neonatal sepsis. Despite aggressive symptomatic and supportive treatment of the infant based on laboratory tests and clinical practice, the infant eventually died. This is the first case of meningoencephalitis due to serotype O75 reported in China. The presence of highly pathogenic multidrug-resistant microorganisms isolated in neonates underscores the need to implement rapid resistance diagnostic methods and should prompt consideration of alternatives to empiric treatment of neonatal bacterial meningitis.

Early osteoarthritis diagnosis based on near-infrared spectroscopy combined with aquaphotomics.

Osteoarthritis (OA) is the most common joint disease and the leading cause of disability in elderly individuals. Despite rapid advances in imaging techniques, early OA diagnosis remains a clinical challenge. In the present study, the feasibility of early OA diagnosis was explored via near-infrared spectroscopy (NIRS) combined with aquaphotomics. Synovial fluid samples from 65 cases of OA categorized as mild, moderate, and severe according to theKellgrenandLawrence classification criteria were analyzed via NIRS. The 1st overtone of water (1300-1600 nm) was considered as the research object for an aquaphotomics model, and aquagrams of the mild, moderate, and severe OA cases were generated using 12 water absorption patterns for early OA diagnosis.The aquaphotomics results exhibited clear differences in the region of 1300-1500 nm, and the number of hydrogen bonds of different water species (1412,1424, 1482, and 1496 nm) evidently correlated with OA occurrence and development. With OA progression, the absorption intensity of water molecules without hydrogen bonds (1412 nm/1424 nm) became stronger, while the absorption intensity of water molecules with four hydrogen bonds (1482 nm/1496 nm) decreased.These results together reveal that the established accurate and rapid early OA diagnosis model based on NIRS combined with aquaphotomics is effective and feasible, and that the number of hydrogen bonds can be used as a biomarker for early OA diagnosis.

Exogenous spraying of IAA improved the efficiency of microspore embryogenesis in Wucai (Brassica campestris L.) by affecting the balance of endogenous hormones, energy metabolism, and cell wall degradation.

BACKGROUND: Microspore embryogenesis is an extraordinarily complicated process, comprehensively regulated by a composite network of physiological and molecular factors, among which hormone is one of the most crucial factors. Auxin is required for stress-induced microspore reprogramming, however, the mechanism of its regulation of microspore embryogenesis is still unclear. RESULTS: In this study, we found exogenously spraying 100 mg·L- 1 IAA on the buds of Wucai significantly increased the rate of microspore embryogenesis, and moreover accelerated the process of embryogenesis. Physiological and biochemical tests showed that the contents of amino acids, soluble total sugar, soluble protein, and starch were significantly increased after IAA treatment. Furthermore, exogenously spraying 100 mg·L- 1 IAA significantly enhanced IAA, GA4, and GA9 content, increased catalase (CAT) and malondialdehyde (MDA) activity, and reduced abscisic acid (ABA), MDA and soluble protopectin content, H2O2 and O2·- production rate in the bud with the largest population of late-uninucleate-stage microspores. Transcriptome sequencing was performed on buds respectively treated with 100 mg·L- 1 IAA and fresh water. A total of 2004 DEGs were identified, of which 79 were involved in micropores development, embryonic development and cell wall formation and modification, most of which were upregulated. KEGG and GO analysis revealed that 9.52% of DEGs were enriched in plant hormone synthesis and signal transduction pathways, pentose and glucuronic acid exchange pathways, and oxidative phosphorylation pathways. CONCLUSIONS: These findings indicated that exogenous IAA altered the contents of endogenous hormone content, total soluble sugar, amino acid, starch, soluble protein, MDA and protopectin, the activities of CAT and peroxidase (POD), and the production rate of H2O2 and O2·-. Combined with transcriptome analysis, it was found that most genes related to gibberellin (GA) and Auxin (IAA) synthesis and signal transduction, pectin methylase (PME) and polygalacturonase (PGs) genes and genes related to ATP synthesis and electron transport chain were upregulated, and genes related to ABA synthesis and signal transduction were downregulated. These results indicated that exogenous IAA treatment could change the balance of endogenous hormones, accelerate cell wall degradation, promote ATP synthesis and nutrient accumulation, inhibit ROS accumulation, which ultimately promote microspore embryogenesis.

RPS15 interacted with IGF2BP1 to promote esophageal squamous cell carcinoma development via recognizing m6A modification.

Increased rates of ribosome biogenesis have been recognized as hallmarks of many cancers and are associated with poor prognosis. Using a CRISPR synergistic activation mediator (SAM) system library targeting 89 ribosomal proteins (RPs) to screen for the most oncogenic functional RPs in human esophageal squamous cell carcinoma (ESCC), we found that high expression of RPS15 correlates with malignant phenotype and poor prognosis of ESCC. Gain and loss of function models revealed that RPS15 promotes ESCC cell metastasis and proliferation, both in vitro and in vivo. Mechanistic investigations demonstrated that RPS15 interacts with the K homology domain of insulin-like growth factor 2 mRNA-binding protein 1 (IGF2BP1), which recognizes and directly binds the 3'-UTR of MKK6 and MAPK14 mRNA in an m6A-dependent manner, and promotes translation of core p38 MAPK pathway proteins. By combining targeted drug virtual screening and functional assays, we found that folic acid showed a therapeutic effect on ESCC by targeting RPS15, which was augmented by the combination with cisplatin. Inhibition of RPS15 by folic acid, IGF2BP1 ablation, or SB203580 treatment were able to suppress ESCC metastasis and proliferation via the p38 MAPK signaling pathway. Thus, RPS15 promotes ESCC progression via the p38 MAPK pathway and RPS15 inhibitors may serve as potential anti-ESCC drugs.