Nirmatrelvir/ritonavir treatment of patients with COVID-19 taking tacrolimus: case series describing the results of drug-drug interactions.

Nirmatrelvir/ritonavir is a novel drug combination that is authorized by the Food and Drug Administration for the treatment of coronavirus disease 2019 (COVID-19). Ritonavir is a cytochrome P450 3A inhibitor and a P-glycoprotein inhibitor that increases the plasma concentration of tacrolimus and other medications. We describe the cases of two patients treated with nirmatrelvir/ritonavir: a patient who had undergone kidney transplantation and another with a history of hematopoietic stem cell transplantation. Toxic concentrations of tacrolimus were induced in both. This case series highlights the risk associated with the concomitant administration of tacrolimus and nirmatrelvir/ritonavir.

Contributing Factors Affecting the Length of Hospital Stay among Febrile Patients with Omicron Reported in Suzhou.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has had global attention with regard to the urgent challenging threat to global public health. Currently, the novel Omicron variant is showing rapid transmission across the world, which appears to be more contagious than the previous variants of COVID-19. Early recognition of disease is critical for patients' prognosis. Fever is the most common symptom. We evaluated the clinical characteristics of febrile patients with COVID-19 reported in Suzhou and explored the predictors for a longer duration of hospitalization in febrile patients. METHODS: This retrospective study was carried out in 146 Omicron variant infected patients confirmed by nucleic acid tests in the Affiliated Infectious Hospital of Soochow University between February 13, 2022 and March 2, 2022. Data of febrile and afebrile laboratory-confirmed patients on hospital admission in Suzhou were collected and compared. According to the median length of stay (LOS), febrile cases were divided into short and long LOS groups. Then the predictive factors for a prolonged duration of hospitalization were analyzed using logistic regression methods. Receiver Operating Characteristic (ROC) Curve analysis was used to analyze the effectiveness of the risk factors for prolonged duration of hospitalization in febrile COVID-19 patients. RESULTS: Of the 146 discharged patients in our study, 112 patients (76.7%) caught a fever. Compared to afebrile Omicron patients, febrile patients showed a significantly longer duration of hospitalization (15.00 (5.80) vs. 13.00 (6.00), p = 0.002). Taking the median LOS (15 days) as the dividing point, 64 febrile cases were assigned to the short LOS group and the rest to the long LOS group. The long LOS group had a longer virus shedding duration than the short LOS group (18.42 ± 2.86 vs. 11.94 ± 2.50 days, p < 0.001). Compared to short LOS febrile patients, long LOS patients were older (44.88 ± 21.36 vs. 30.89 ± 17.95 years, p < 0.001) and showed a higher proportion of greater than 60 years old (33.3% vs. 9.4%, p = 0.002; Supplemental Table S2). Febrile patients with long LOS also showed a higher proportion of hypertension (25% vs. 6.3%, p = 0.005) and higher levels of cTnI (5.00 (3.00) vs. 4.00 (2.00) µg/L, p = 0.025). The multivariate analysis indicated that virus shedding duration (OR 2.369, 95% CI 1.684 - 3.333, p < 0.001) was the independent risk factor associated with long-term hospital stay in febrile patients with Omicron. Furthermore, ROC Curve analysis revealed that the area under the curve (AUC) for virus shedding duration to diagnose prolonged duration of hospitalization in febrile COVID-19 patients was 0.951 (95% CI 0.913 - 0.989). The cutoff point was set at 14.5 days. CONCLUSIONS: More than half of the non-severe patients exposed to the new Omicron variant had symptoms of fever. In total, 42.86% of the febrile patients were discharged within 15 days since hospital admission. Febrile Omicron cases took a longer duration of hospitalization compared to afebrile patients, and virus shedding duration (OR 2.369, 95% CI 1.684 - 3.333, p < 0.001) was probably a predictive factor for long-term hospital stays.

Determination of insecticide residues in beverages based on MIL-100(Fe) dispersive solid-phase microextraction in combination with dispersive liquid-liquid microextraction followed by HPLC-MS/MS.

A novel dispersive solid-phase microextraction method based on a metal-organic framework (MIL-100(Fe)) combined with a dispersive liquid-liquid microextraction technique was proposed for the extraction and enrichment of four insecticides in beverages. The qualitative and quantitative analysis of these insecticides was conducted using HPLC-MS/MS. To optimize the extraction process, several parameters were investigated, and the main variables were optimized using CCD-based RSM. The developed method displayed a wide linear range of 1.000-1000 ng/L and R2 values >0.993 for all four calibration curves. The method demonstrated high sensitivity, with LODs and LOQs of 0.3-0.6 ng/L and 0.8-1.0 ng/L, respectively. In addition, the greenness of the proposed method was assessed using the Complex GAPI tool, and the results showed that the proposed method exhibits benefits, such as minimal usage of organic solvents and negligible matrix influence, making it a suitable method for the detection of insecticide residues in beverages.

Separation and Detection of Catechins and Epicatechins in Shanxi Aged Vinegar Using Solid-Phase Extraction and Hydrophobic Deep Eutectic Solvents Combined with HPLC.

This research presents a new, eco-friendly, and swift method combining solid-phase extraction and hydrophobic deep eutectic solvents (DES) with high-performance liquid chromatography (SPE-DES-HPLC) for extracting and quantifying catechin and epicatechin in Shanxi aged vinegar (SAV). The parameters, such as the elution solvent type, the XAD-2 macroporous resin dosage, the DES ratio, the DES volume, the adsorption time, and the desorption time, were optimized via a one-way experiment. A central composite design using the Box-Behnken methodology was employed to investigate the effects of various factors, including 17 experimental runs and the construction of three-dimensional response surface plots to identify the optimal conditions. The results show that the optimal conditions were an HDES (tetraethylammonium chloride and octanoic acid) ratio of 1:3, an XAD-2 macroporous resin dosage of 188 mg, and an adsorption time of 11 min. Under these optimal conditions, the coefficients of determination of the method were greater than or equal to 0.9917, the precision was less than 5%, and the recoveries ranged from 98.8% to 118.8%. The environmentally friendly nature of the analytical process and sample preparation was assessed via the Analytical Eco-Scale and AGREE, demonstrating that this method is a practical and eco-friendly alternative to conventional determination techniques. In summary, this innovative approach offers a solid foundation for the assessment of flavanol compounds present in SAV samples.

Candidate membrane protein gene families related to chemoreception in a wood-boring beetle, Pharsalia antennata Gahan (Coleoptera: Cerambycidae).

The longhorned beetles are key players for the maintenance of biodiversity in the terrestrial ecosystem. As xylophagous cerambycid insects in Coleoptera, the beetles have evolved specialized olfactory and gustatory systems to recognize chemical cues in the surrounding habitats. Despite over 36,000 described species in the Cerambycidae family including a wood-boring pest Pharsalia antennata, only a limited number of them (<1 %) have been characterized regarding their chemical ecology at the molecular level. Here, we surveyed four membrane protein gene families in P. antennata related to chemoreception through transcriptomics, phylogenetics and expression profiling analyses. In total, 144 genes encoding 72 odorant receptors (ORs), 33 gustatory receptors (GRs), 23 ionotropic receptors (IRs), four sensory neuron membrane proteins (SNMPs) and 12 ionotropic glutamate receptors (iGluRs) were harvested from the transcriptome of multiple tissues including antennae and legs of both sexes. The lineage-specific expansion of PantORs possibly implied a diverse range of host plants in this beetle, supporting this correlation between the host range and olfactory receptor repertoire sizes across cerambycid species. Further phylogenetic analysis revealed that Group 2 was contributed mainly to the large OR gene repertoire in P. antennata, representing 18 genes in Group 2A and eight in Group 2B. On the other hand, some key chemosensory genes were identified by applying a phylogenetics approach, such as PantOR21 close to the 2-phenylethanol receptor in Megacyllene caryae, three carbon dioxide GRs and seven Antennal IRs (A-IRs) clades. We also determined sex- and tissue-specific expression profiles of 69 chemosensory genes, revealing the high expression of most PantORs in antennae. Noticeably, 10 sex-biased genes (six PantORs, three PantIRs and PantSNMP1a) were presented in antennae, five sex-biased PantGRs in legs and 39 sex-biased genes (15 PantORs, 13 PantGRs, eight PantIRs and three PantSNMPs) in abdomens. These findings have greatly enhanced our knowledge about the chemical ecology of P. antennata and identify candidate molecular targets for mediating smell and taste of this beetle.

Physicochemical and antioxidant properties of pectin fractions extracted from lemon (Citrus Eureka) peels.

Pectin, a natural polysaccharide, holds versatile applications in food and pharmaceuticals. However, there is a need for further exploration into extracting novel functional fractions and characterizing them thoroughly. In this study, a sequential extraction approach was used to obtain three distinct lemon pectin (LP) fractions from lemon peels (Citrus Eureka): LP extracted with sodium acetate (LP-SA), LP extracted with ethylenediaminetetraacetic acid (LP-EDTA), and LP extracted with sodium carbonate and sodium borohydride (LP-SS). Comprehensive analysis revealed low methyl-esterification in all fractions. LP-SA and LP-SS displayed characteristics of rhamnogalacturonan-I type pectin, while LP-EDTA mainly consisted of homogalacturonan pectin. Notably, LP-SA formed self-aggregated particles with rough surfaces, LP-EDTA showed interlocking linear structures with smooth planes, and LP-SS exhibited branch chain structures with smooth surfaces. Bioactivity analysis indicated that LP-SA had significant apparent viscosity and ABTS radical scavenging activity, while both LP-EDTA and LP-SS showed excellent thermal stability according to thermogravimetric analysis (TGA). Furthermore, LP-SS exhibited remarkable gel-forming ability and significant hydroxyl free radicals scavenging activity. In conclusion, this study presents a novel method for extracting various lemon pectin fractions with unique structural and bioactive properties, contributing insights for advanced applications in the food and pharmaceutical sectors.

Molecular Determinant Underlying Selective Coupling of Primary G-Protein by Class A GPCRs.

G-protein-coupled receptors (GPCRs) transmit downstream signals predominantly via G-protein pathways. However, the conformational basis of selective coupling of primary G-protein remains elusive. Histamine receptors H2R and H3R couple with Gs- or Gi-proteins respectively. Here, three cryo-EM structures of H2R-Gs and H3R-Gi complexes are presented at a global resolution of 2.6-2.7 Å. These structures reveal the unique binding pose for endogenous histamine in H3R, wherein the amino group interacts with E2065.46 of H3R instead of the conserved D1143.32 of other aminergic receptors. Furthermore, comparative analysis of the H2R-Gs and H3R-Gi complexes reveals that the structural geometry of TM5/TM6 determines the primary G-protein selectivity in histamine receptors. Machine learning (ML)-based structuromic profiling and functional analysis of class A GPCR-G-protein complexes illustrate that TM5 length, TM5 tilt, and TM6 outward movement are key determinants of the Gs and Gi/o selectivity among the whole Class A family. Collectively, the findings uncover the common structural geometry within class A GPCRs that determines the primary Gs- and Gi/o-coupling selectivity.

Gut microbiota intervention alleviates pulmonary inflammation in broilers exposed to fine particulate matter from broiler house.

The gut microbiota of poultry is influenced by a variety of factors, including feed, drinking water, airborne dust, and footpads, among others. Gut microbiota can affect the immune reaction and inflammation in the lungs. To investigate the effect of gut microbiota variation on lung inflammation induced by PM2.5 (fine particulate matter) in broilers, 36 Arbor Acres (AA) broilers were randomly assigned to three groups: control group (CON), PM2.5 exposure group (PM), and PM2.5 exposure plus oral antibiotics group (PMA). We used non-absorbable antibiotics (ABX: neomycin and amikacin) to modify the microbiota composition in the PMA group. The intervention was conducted from the 18th to the 28th day of age. Broilers in the PM and PMA groups were exposed to PM by a systemic exposure method from 21 to 28 days old, and the concentration of PM2.5 was controlled at 2 mg/m3. At 28 days old, the lung injury score, relative mRNA expression of inflammatory factors, T-cell differentiation, and dendritic cell function were significantly increased in the PM group compared to the CON group, and those of the PMA group were significantly decreased compared to the PM group. There were significant differences in both α and ß diversity of cecal microbiota among these three groups. Numerous bacterial genera showed significant differences in relative abundance among the three groups. In conclusion, gut microbiota could affect PM2.5-induced lung inflammation in broilers by adjusting the capacity of antigen-presenting cells to activate T-cell differentiation. IMPORTANCE: Gut microbes can influence the development of lung inflammation, and fine particulate matter collected from broiler houses can lead to lung inflammation in broilers. In this study, we explored the effect of gut microbes modified by intestinal non-absorbable antibiotics on particulate matter-induced lung inflammation. The results showed that modification in the composition of gut microbiota could alleviate lung inflammation by attenuating the ability of dendritic cells to stimulate T-cell differentiation, which provides a new way to protect lung health in poultry farms.

Intelligent classification of major depressive disorder using rs-fMRI of the posterior cingulate cortex.

Major Depressive Disorder (MDD) is a widespread psychiatric condition that affects a significant portion of the global population. The classification and diagnosis of MDD is crucial for effective treatment. Traditional methods, based on clinical assessment, are subjective and rely on healthcare professionals' expertise. Recently, there's growing interest in using Resting-State Functional Magnetic Resonance Imaging (rs-fMRI) to objectively understand MDD's neurobiology, complementing traditional diagnostics. The posterior cingulate cortex (PCC) is a pivotal brain region implicated in MDD which could be used to identify MDD from healthy controls. Thus, this study presents an intelligent approach based on rs-fMRI data to enhance the classification of MDD. Original rs-fMRI data were collected from a cohort of 430 participants, comprising 197 patients and 233 healthy controls. Subsequently, the data underwent preprocessing using DPARSF, and the amplitudes of low-frequency fluctuation values were computed to reduce data dimensionality and feature count. Then data associated with the PCC were extracted. After eliminating redundant features, various types of Support Vector Machines (SVMs) were employed as classifiers for intelligent categorization. Ultimately, we compared the performance of each algorithm, along with its respective optimal classifier, based on classification accuracy, true positive rate, and the area under the receiver operating characteristic curve (AUC-ROC). Upon analyzing the comparison results, we determined that the Random Forest (RF) algorithm, in conjunction with a sophisticated Gaussian SVM classifier, demonstrated the highest performance. Remarkably, this combination achieved a classification accuracy of 81.9 % and a true positive rate of 92.9 %. In conclusion, our study improves the classification of MDD by supplementing traditional methods with rs-fMRI and machine learning techniques, offering deeper neurobiological insights and aiding accuracy, while emphasizing its role as an adjunct to clinical assessment.

[Quality control of Tianwang Buxin Pills based on UPLC fingerprint and multi-component quantification].

Tianwang Buxin Pills have demonstrated therapeutic effects in clinical practice, whereas there is a serious lack of comprehensive quality control to ensure the safety and effectiveness of clinical medication. In this study, ultra-performance liquid chromatography(UPLC) was employed to establish the fingerprint and the method for simultaneously determining the content of seven components of Tianwang Buxin Pills. Furthermore, chemometrics was employed to identify the key factors for the stable quality, which provided a reference for the comprehensive quality control and evaluation of this preparation. There were 25 common peaks in the UPLC fingerprints of 15 batches of Tianwang Buxin Pills, from which thirteen compounds were identified. A quantitation method was established for seven pharmacological components(α-linolenic acid, salvianolic acid B, glycyrrhetinic acid, schisandrin A, ß-asarone, 3,6'-disinapoylsucrose, and ligustilide). The principal component analysis(PCA) and partial least square discriminate analysis(PLS-DA) were performed to determine the key pharmacological components for controlling the quality stability of Tianwang Buxin Pills, which included 3,6'-disinapoylsucrose, α-linolenic acid, and ß-asarone. The established fingerprint and multi-component content determination method have strong specificity, stability, and reliability. In addition, 3,6'-disinapoylsucrose, α-linolenic acid, and ß-asarone are the key pharmacological components that ensure the quality stability between batches and can be used to comprehensively control the quality of Tianwang Buxin Pills. The findings provide a scientific basis for the quality evaluation and standard establishment of Tianwang Buxin Pills.

Misdiagnosis of synovial sarcoma - cellular myofibroma with SRF-RELA gene fusion: A case report.

BACKGROUND: Cellular myofibroma is a rare subtype of myofibroma that was first described in 2017. Its diagnosis is often challenging because of its relative rarity, lack of known genetic abnormalities, and expression of muscle markers that can be confused with sarcomas that have myogenic differentiation. Currently, scholars have limited knowledge of this disease, and published cases are few. Further accumulation of diagnostic and treatment experiences is required. CASE SUMMARY: A 16-year-old girl experienced left upper limb swelling for 3 years. She sought medical attention at a local hospital 10 months ago, where magnetic resonance imaging revealed a 5-cm soft tissue mass. Needle biopsy performed at a local hospital resulted in the diagnosis of a spindle cell soft tissue sarcoma. The patient was referred to our hospital for limb salvage surgery with endoprosthetic replacement. She was initially diagnosed with a synovial sarcoma. Consequently, clinical management with chemotherapy was continued for the malignant sarcoma. Our pathology department also performed fluorescence in situ hybridization for result validation, which returned negative for SS18 gene breaks, indicating that it was not a synovial sarcoma. Next-generation sequencing was used to identify the SRF-RELA rearrangement. The final pathological diagnosis was a cellular/myofibroblastic neoplasm with an SRF-RELA gene fusion. The patient had initially received two courses of chemotherapy; however, chemotherapy was discontinued after the final diagnosis. CONCLUSION: This case was misdiagnosed because of its rare occurrence, benign biological behavior, and pathological similarity to soft tissue sarcoma.

Multivariate analysis for data mining to characterize poultry house environment in winter.

The processing and analysis of massive high-dimensional datasets are important issues in precision livestock farming (PLF). This study explored the use of multivariate analysis tools to analyze environmental data from multiple sensors located throughout a broiler house. An experiment was conducted to collect a comprehensive set of environmental data including particulate matter (TSP, PM10, and PM2.5), ammonia, carbon dioxide, air temperature, relative humidity, and in-cage and aisle wind speeds from 60 locations in a typical commercial broiler house. The dataset was divided into 3 growth phases (wk 1-3, 4-6, and 7-9). Spearman's correlation analysis and principal component analysis (PCA) were used to investigate the latent associations between environmental variables resulting in the identification of variables that played important roles in indoor air quality. Three cluster analysis methods; k-means, k-medoids, and fuzzy c-means cluster analysis (FCM), were used to group the measured parameters based on their environmental impact in the broiler house. In general, the Spearman and PCA results showed that the in-cage wind speed, aisle wind speed, and relative humidity played critical roles in indoor air quality distribution during broiler rearing. All 3 clustering methods were found to be suitable for grouping data, with FCM outperforming the other 2. Using data clustering, the broiler house spaces were divided into 3, 2, and 2 subspaces (clusters) for wk 1 to 3, 4 to 6, and 7 to 9, respectively. The subspace in the center of the house had a poorer air quality than other subspaces.

The gut microbiome modulates the susceptibility to traumatic stress in a sex-dependent manner.

Post-traumatic stress disorder (PTSD), a psychological condition triggered by exposure to extreme or chronic stressful events, exhibits a sex bias in incidence and clinical manifestations. Emerging research implicates the gut microbiome in the pathogenesis of PTSD and its roles in stress susceptibility. However, it is unclear whether differential gut microbiota contribute to PTSD susceptibility in male and female rats. Here, we utilized the single prolonged stress animal model and employed unsupervised machine learning to classify stressed animals into stress-susceptible subgroups and stress-resilient subgroups. Subsequently, using 16S V3-V4 rDNA sequencing, we investigated the differential gut microbiota alterations between susceptible and resilient individuals in male and female rats. Our findings revealed distinct changes in gut microbiota composition between the sexes at different taxonomic levels. Furthermore, the abundance of Parabacteroides was lower in rats that underwent SPS modeling compared to the control group. In addition, the abundance of Tenericutes in the stress-susceptible subgroup was higher than that in the control group and stress-resilient subgroup, suggesting that Tenericutes may be able to characterize stress susceptibility. What is particularly interesting here is that Cyanobacteria may be particularly associated with anti-anxiety effects in male rats. This study underscores sex-specific variations in gut microbiota composition in response to stress and sex differences should be taken into account when using macrobiotics for neuropsychiatric treatment, highlighting potential targets for PTSD therapeutic interventions.

Structure-based design of non-hypertrophic apelin receptor modulator.

Apelin is a key hormone in cardiovascular homeostasis that activates the apelin receptor (APLNR), which is regarded as a promising therapeutic target for cardiovascular disease. However, adverse effects through the ß-arrestin pathway limit its pharmacological use. Here, we report cryoelectron microscopy (cryo-EM) structures of APLNR-Gi1 complexes bound to three agonists with divergent signaling profiles. Combined with functional assays, we have identified "twin hotspots" in APLNR as key determinants for signaling bias, guiding the rational design of two exclusive G-protein-biased agonists WN353 and WN561. Cryo-EM structures of WN353- and WN561-stimulated APLNR-G protein complexes further confirm that the designed ligands adopt the desired poses. Pathophysiological experiments have provided evidence that WN561 demonstrates superior therapeutic effects against cardiac hypertrophy and reduced adverse effects compared with the established APLNR agonists. In summary, our designed APLNR modulator may facilitate the development of next-generation cardiovascular medications.

Effectiveness of Mobile Health Platform-Based Continuity of Care in Osteoporosis Prevention and Treatment.

Objective: To assess the effectiveness of using mobile health platforms for continuous care in preventing and treating osteoporosis. Methods: 114 patients with osteoporosis admitted to Nantong First People's Hospital from March 2021 to June 2022 were recruited and assigned equally via random number table method to receive either routine care (namely education on osteoporosis disease, dietary guidance, exercise guidance, activity guidance, medication supervision, fall prevention, psychological care, and secondary health education at the time of discharge) (routine group) or mobile health platform-based continuity of care (continuity group), with 57 patients in each group. Outcome measures included treatment compliance, disease knowledge of osteoporosis (diet, exercise, risk factors), quality of life level, and care satisfaction. Results: All eligible patients were followed up for one year after discharge from the hospital. Patients with continuity of care showed higher treatment compliance and disease knowledge of diet, exercise, and risk factors than those with routine care (P = .004). Continuity of care was associated with significantly higher MOS 36-item short-form health survey (SF-36) scores (The SF-36 is a self-administered questionnaire containing 36 items that survey overall health status) and nursing satisfaction in patients versus routine care (P = .004). Conclusion: Mobile health platform-based continuity of care effectively enhances post-discharge compliance and knowledge of osteoporosis in patients with osteoporosis, thereby improving post-discharge quality of life and satisfaction with care. Multi-center studies involving diverse healthcare settings and patient populations would provide more robust evidence. Moreover, these findings highlight the potential benefits of incorporating mobile health platforms into the care continuum for osteoporosis patients. Also, by utilizing mobile health platforms, healthcare providers can extend their reach beyond hospital settings and provide continuous care and support to patients, potentially reducing the burden on healthcare systems and improving overall population health outcomes.

NTPDase1-ATP-P2Y2Rs axis in the sciatic nerve contributes to acupuncture at "Zusanli" (ST36)-induced analgesia in ankle arthritis rats.

BACKGROUND: The efficacy of acupuncture at Zusanli (ST36) in alleviating lower-limb pain is widely acknowledged in clinical practice, while its underlying mechanism remains incompletely elucidated. Our previous research had revealed that the prompt analgesia induced by needling-ST36 was accompanied by expression alterations in certain exco-nucleotidases within the sciatic nerve. Building upon this finding, the current work focused on NTPDase1, the primary ecto-nucleotidase in the human body, which converts ATP into AMP. METHODS: A 20-min acupuncture was administered unilaterally at the ST36 on rats with acute ankle arthritis. The pain thresholds of the injured hind paws were determined. Pharmacological interference was carried out by introducing the corresponding reagents to the sciatic nerve. ATP levels around the excised nerve were measured using a luciferase-luciferin assay. Live calcium imaging, utilizing the Fura 2-related-F340/F380 ratio, was conducted on Schwann cells in excised nerves and cultured rat SCs line, RSC96 cells. RESULTS: The analgesic effect induced by needling-ST36 was impaired when preventing ATP degradation via inhibiting NTPDase1 activities with ARL67156 or Ticlopidine. Conversely, increasing NTPDase1 activities with Apyrase duplicated the acupuncture effect. Similarly, preventing the conversion of AMP to adenosine via suppression of NT5E with AMP-CP hindered the acupuncture effect. Unexpectedly, impeded ATP hydrolysis ability and diminished NTPDase1 expression were observed in the treated group. Agonism at P2Y2Rs with ATP, UTP, or INS365 resulted in anti-nociception. Contrarily, antagonism at P2Y2Rs with Suramin or AR-C 118925xx prevented acupuncture analgesia. Immunofluorescent labeling demonstrated that the treated rats expressed more P2Y2Rs that were predominant in Schwann cells. Suppression of Schwann cells by inhibiting ErbB receptors also prevented acupuncture analgesia. Finally, living imaging on the excised nerves or RSC96 cells showed that agonism at P2Y2Rs indeed led to [Ca2+]i rise. CONCLUSION: These findings strongly suggest that the analgesic mechanism of needling-ST36 on the hypersensation in the lower limb partially relies on NTPDase1 activities in the sciatic nerve. In addition to facilitating adenosine signaling in conjunction with NT5E, most importantly, NTPDase1 may provide an appropriate low-level ATP milieu for the activation of P2Y2R in the sciatic nerve, particularly in Schwann cells.

Automated machine learning for the identification of asymptomatic COVID-19 carriers based on chest CT images.

BACKGROUND: Asymptomatic COVID-19 carriers with normal chest computed tomography (CT) scans have perpetuated the ongoing pandemic of this disease. This retrospective study aimed to use automated machine learning (AutoML) to develop a prediction model based on CT characteristics for the identification of asymptomatic carriers. METHODS: Asymptomatic carriers were from Yangzhou Third People's Hospital from August 1st, 2020, to March 31st, 2021, and the control group included a healthy population from a nonepizootic area with two negative RT‒PCR results within 48 h. All CT images were preprocessed using MATLAB. Model development and validation were conducted in R with the H2O package. The models were built based on six algorithms, e.g., random forest and deep neural network (DNN), and a training set (n = 691). The models were improved by automatically adjusting hyperparameters for an internal validation set (n = 306). The performance of the obtained models was evaluated based on a dataset from Suzhou (n = 178) using the area under the curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and F1 score. RESULTS: A total of 1,175 images were preprocessed with high stability. Six models were developed, and the performance of the DNN model ranked first, with an AUC value of 0.898 for the test set. The sensitivity, specificity, PPV, NPV, F1 score and accuracy of the DNN model were 0.820, 0.854, 0.849, 0.826, 0.834 and 0.837, respectively. A plot of a local interpretable model-agnostic explanation demonstrated how different variables worked in identifying asymptomatic carriers. CONCLUSIONS: Our study demonstrates that AutoML models based on CT images can be used to identify asymptomatic carriers. The most promising model for clinical implementation is the DNN-algorithm-based model.

The exposure in ovo to glyphosate on the integrity of intestinal epithelial tight junctions of chicks.

Glyphosate is an ingredient widely used in various commercial formulations, including Roundup®. This study focused on tight junctions and the expression of inflammatory genes in the small intestine of chicks. On the sixth day of embryonic development, the eggs were randomly assigned to three groups: the control group (CON, n = 60), the glyphosate group (GLYP, n = 60), which received 10 mg of active glyphosate/kg egg mass, and the Roundup®-based glyphosate group also received 10 mg of glyphosate. The results indicated that the chicks exposed to glyphosate or Roundup® exhibited signs of oxidative stress. Additionally, histopathological alterations in the small intestine tissues included villi fusion, complete fusion of some intestinal villi, a reduced number of goblet cells, and necrosis of some submucosal epithelial cells in chicks. Genes related to the small intestine (ZO-1, ZO-2, Claudin-1, Claudin-3, JAM2, and Occludin), as well as the levels of pro-inflammatory cytokines (IFNγ, IL-1ß, and IL-6), exhibited significant changes in the groups exposed to glyphosate or Roundup® compared to the control group. In conclusion, the toxicity of pure glyphosate or Roundup® likely disrupts the small intestine of chicks by modulating the expression of genes associated with tight junctions in the small intestine.

Nanopore sequencing of infectious fluid is a promising supplement for gold-standard culture in real-world clinical scenario.

Introduction: Infectious diseases are major causes of morbidity and mortality worldwide, necessitating the rapid identification and accurate diagnosis of pathogens. While unbiased metagenomic next-generation sequencing (mNGS) has been extensively utilized in clinical pathogen identification and scientific microbiome detection, there is limited research about the application of nanopore platform-based mNGS in the diagnostic performance of various infectious fluid samples. Methods: In this study, we collected 297 suspected infectious fluids from 10 clinical centers and detected them with conventional microbiology culture and nanopore platform-based mNGS. The objective was to assess detective and diagnostic performance of nanopore-sequencing technology (NST) in real-world scenarios. Results: Combined with gold-standard culture and clinical adjudication, nanopore sequencing demonstrated nearly 100% positive predictive agreements in microbial-colonized sites, such as the respiratory and urinary tracts. For samples collected from initially sterile body sites, the detected microorganisms were highly suspected pathogens, and the negative predictive agreements were relatively higher than those in the microbial-colonized sites, particularly with 100% in abscess and 95.7% in cerebrospinal fluid. Furthermore, consistent performance was also observed in the identification of antimicrobial resistance genes and drug susceptibility testing of pathogenic strains of Escherichia coli, Staphylococcus aureus, and Acinetobacter baumannii. Discussion: Rapid NST is a promising clinical tool to supplement gold-standard culture, and it has the potential improve patient prognosis and facilitate clinical treatment of infectious diseases.

Demystifying the landscape of endometrial immune microenvironment in luteal-phase from cuprotosis: Implications for the mechanism and treatment of RPL.

BACKGROUND: Adaptive changes in the endometrial immune microenvironment during the luteal phase are essential for pregnancy, and their abnormalities are associated with recurrent pregnancy loss (RPL). Nevertheless, the specific mechanism is still unknown. Cuprotosis, an innovatively discovered type of programmed cell death, provides us with a pioneering perspective to decipher the landscape of luteal-phase endometrial immune microenvironment in RPL. This study aimed to analyze the immune landscape of luteal-phase endometrial microenvironment in RPL and explore the association of cuprotosis with it through integrative bioinformatics analysis. METHODS: The microarrays involving the luteal phase endometrial tissue of RPL were obtained from the GEO database. Differentially expressed genes (DEGs) of RPL were screened and key modules were detected by WGCNA. GO, KEGG, and GSEA immune enrichment analyses were performed on the DEGs in the most relevant modules to RPL. Then, the endometrial immune microenvironment landscape of RPL was analyzed, including immune infiltration analysis and correlation analysis between immune cells or immune functions. The interaction of cuprotosis-related genes (CRGs), the expression level between groups, the immune localization and their correlation with immune cells and immune function were analyzed. LASSO regression and Nomogram evaluated the diagnostic value of immune-related CRGS in RPL. Functional enrichment analysis was performed on the RPL signature CRGs. And RPL samples were grouped according to the expression of 7 RPL signature CRGs through unsupervised clustering analysis. After that, we analyzed the expression level of CRGs and immune infiltration, as well as performed immune function enrichment analysis in subtypes. In addition, we also screened potential drugs that might act on CRGs to improve the pathological mechanism of RPL. RESULTS: In this study, we uncovered that DEGs and genes in key modules derived from weighted gene co-expression network analysis (WGCNA) were involved in immune regulation. And the immune infiltration landscape of RPL was significantly different from healthy controls. Furthermore, six hub genes were screened from CRGs based on Cytohubba, and their expression profilings were verified in RPL and normal mouse samples. Besides, seven CRGs closely associated with the immune regulation of RPL were identified by Spearman correlation analysis, including SLC31A1, LIAS, DLD, DLAT, DBT, ATP7B, and ATP7A, named as immune-related CRGs. Furthermore, three subgroups clustered according to these seven genes showed significant differences in immune landscape, suggesting a remarkable effect of CRGs on immune regulation. Last but not least, we analyzed the regulation network of transcription factors, miRNAs, and CRGs, and screened potential compounds for the treatment of RPL by targeting CRGs. CONCLUSIONS: The abnormal endometrial immune microenvironment in the luteal phase was associated with the pathomechanism of RPL, and cuprotosis was closely involved in the immune microenvironment in the luteal phase endometrium of RPL. Collectively, this study revealed the potential contribution of CRGs to the pathogenesis of RPL, providing a novel breakthroughs in insights into the pathogenesis, diagnosis, and treatment of RPL.