ObjectiveTo establish a model that can quickly identify the aroma components in different parts of Nardostachys jatamansi， so as to provide a quality control basis for the market circulation and clinical use of N. jatamansi. MethodsHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） combined with Smart aroma database and National Institute of Standards and Technology（NIST） database were used to characterize the aroma components in different parts of N. jatamansi， and the aroma components were quantified according to relative response factor（RRF） and three internal standards， and the markers of aroma differences in different parts of N. jatamansi were identified by orthogonal partial least squares-discriminant analysis（OPLS-DA） and cluster thermal analysis based on variable importance in the projection（VIP） value >1 and P<0.01. The odor data of different parts of N. jatamansi were collected by Heracles Ⅱ Neo ultra-fast gas phase electronic nose， and the correlation between compound types of aroma components collected by the ultra-fast gas phase electronic nose and the detection results of HS-SPME-GC-MS was investigated by drawing odor fingerprints and odor response radargrams. Chromatographic peak information with distinguishing ability≥0.700 and peak area≥200 was selected as sensor data， and the rapid identification model of different parts of N. jatamansi was established by principal component analysis（PCA）， discriminant factor alysis（DFA）， soft independent modeling of class analogies（SIMCA） and statistical quality control analysis（SQCA）. ResultsThe HS-SPME-GC-MS results showed that there were 28 common components in the underground and aboveground parts of N. jatamansi， of which 22 could be quantified and 12 significantly different components were screened out. Among these 12 components， the contents of five components（ethyl isovalerate， 2-pentylfuran， benzyl alcohol， nonanal and glacial acetic acid，） in the aboveground part of N. jatamansi were significantly higher than those in the underground part（P<0.01）， the contents of β-ionone， patchouli alcohol， α-caryophyllene， linalyl butyrate， valencene， 1，8-cineole and p-cymene in the underground part of N. jatamansi were significantly higher than those in the aboveground part（P<0.01）. Heracles Ⅱ Neo electronic nose results showed that the PCA discrimination index of the underground and aboveground parts of N. jatamansi was 82， and the contribution rates of the principal component factors were 99.94% and 99.89% when 2 and 3 principal components were extracted， respectively. The contribution rate of the discriminant factor 1 of the DFA model constructed on the basis of PCA was 100%， the validation score of the SIMCA model for discrimination of the two parts was 99， and SQCA could clearly distinguish different parts of N. jatamansi. ConclusionHS-SPME-GC-MS can clarify the differential markers of underground and aboveground parts of N. jatamansi. The four analytical models provided by Heracles Ⅱ Neo electronic nose（PCA， DFA， SIMCA and SQCA） can realize the rapid identification of different parts of N. jatamansi. Combining the two results， it is speculated that terpenes and carboxylic acids may be the main factors contributing to the difference in aroma between the underground and aboveground parts of N. jatamansi.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.

Hypercoagulable state (HCS) after kidney transplantation is one of the common and serious complications in kidney transplant recipients, which has attracted increasing attention in recent years. HCS refers to the abnormal and excessive activation of blood coagulation function, leading to the increased risk of thrombosis. After kidney transplantation, the combined effects of hemodynamic changes, surgical trauma and severe rejection increase the incidence of HCS, not only raising the risk of thrombosis but also potentially causing graft failure and affecting the postoperative survival rate of patients. This article reviews the influencing factors, clinical manifestations, diagnostic methods and preventive strategies of HCS after kidney transplantation, aiming to provide a theoretical basis for optimizing perioperative management and improving the prognosis of patients.

Intermittent theta burst stimulation (iTBS), a time-saving and cost-effective repetitive transcranial magnetic stimulation regime, has been shown to improve cognition in patients with Alzheimer's disease (AD). However, the specific mechanism underlying iTBS-induced cognitive enhancement remains unknown. Previous studies suggested that mitochondrial functions are modulated by magnetic stimulation. Here, we showed that iTBS upregulates the expression of iron-sulfur cluster assembly 1 (ISCA1, an essential regulatory factor for mitochondrial respiration) in the brain of APP/PS1 mice. In vivo and in vitro studies revealed that iTBS modulates mitochondrial iron-sulfur cluster assembly to facilitate mitochondrial respiration and function, which is required for ISCA1. Moreover, iTBS rescues cognitive decline and attenuates AD-type pathologies in APP/PS1 mice. The present study uncovers a novel mechanism by which iTBS modulates mitochondrial respiration and function via ISCA1-mediated iron-sulfur cluster assembly to alleviate cognitive impairments and pathologies in AD. We provide the mechanistic target of iTBS that warrants its therapeutic potential for AD patients.
Humans ; Mice ; Animals ; Transcranial Magnetic Stimulation ; Alzheimer Disease/therapy* ; Cognitive Dysfunction/therapy* ; Cognition ; Sulfur ; Iron ; Iron-Sulfur Proteins ; Mitochondrial Proteins

ObjectiveTo clone the gene of Marmota himalayana type ‍Ⅰ interferon receptor β subunit （mhIFNAR2）， and to perform antibody preparation and functional identification. MethodsRT-PCR was used for amplification in the spleen tissue of Marmota himalayana to obtain the sequence， which was cloned to the prokaryotic expression vector pRSET-B to express the recombinant protein. Electrophoresis and Western blot were used for identification. BALB/c mice were immunized with the recombinant protein to prepare the polyclonal antibody of its extracellular domain； immunohistochemistry， immunofluorescence assay， and Western Blot were used for identification， and the method of siRNA blockade was used to investigate its function. An analysis of variance was used for comparison of continuous data between multiple groups， and the least significant difference t-test was used for comparison between two groups. ResultsA fragment of mhIFNAR2 （149‍ ‍—‍ ‍1 ‍300 bp） was obtained from spleen tissue， which showed the highest homology of 98.05% in marmot. A prokaryotic expression plasmid was successfully constructed for expression of the extracellular domain of the mhIFNAR2_{（50-181aa）} and was named pRSET-B.mhIFNAR2， and the recombinant protein expressed by this plasmid had a molecular weight of 27 kD， a purity of about 95% after purification， and a concentration of 160 μg/mL. After BALB/c mice were immunized with the purified recombinant protein， 1∶1 000 specific polyclonal antibodies were obtained， and immunohistochemistry and immunofluorescence assay showed the expression in cell membrane and cytoplasm. Among the three siRNAs synthesized， the siRNA starting from the 277 locus （siRNA277） could silence the expression of target genes and weaken the interferon signaling pathway compared with the blank control group and the negative control group （both P<0.05）. ConclusionThe fragment of mhIFNAR2 is obtained， and the polyclonal antibody for the extracellular domain of mhIFNAR2 is successfully prepared， with relatively high titer and specificity， and can be used for immunohistochemistry， immunofluorescence assay， and Western blot.

Human exhaled breath has great application prospects,e.g.,monitoring pharmacokinetics,disease diagnosis,due to its advantages such as non-invasive and high-frequency sampling.Breath samples can be collected from the oral and nasal cavity.However,the oral and nasal environment affect the chemical composition of breath sample.Therefore,the investigation on the chemical composition of mouth-exhaled breath and nose-exhaled breath is crucial for selection of appropriate sampling strategy for individual studies.In this work,secondary electrospray ionization-high resolution mass spectrometry(SESI-HRMS)was applied to analysis of respiratory metabolomics in real time.A quantitative analysis approach was established for 9 kinds of volatile organic compounds(VOCs)e.g.2-butanone,2-pentanone,ethyl acetate,methyl methacrylate,toluene,styrene,mesitylene,isoprene and limonene.The limit of detection was 2.3?240.8 ng/m3.The intra-day(n=6)and inter-day(n=18)relative standard deviations were 0.6%?4.6%and 4.3%?12.2%,respectively.Nine healthy subjects were recruited to investigate the chemical composition of mouth-exhaled and nose-exhaled breath.The results showed the good performance in quantitative analysis of 9 VOCs in breath air.It was found that the number of unique component(m/z)detected in mouth-exhaled breath(167)was 2.2 times greater than that detected in nose-exhaled breath(76),which might result from the complex environment in oral cavity.The signal intensity of commun component(163)was significantly different between mouth-exhaled breath and nose-exhaled breath.Additionally,the elemental composition analysis showed that the proportion of polar compounds detected in nose-exhaled breath was higher than that in mouth-exhaled breath.This study demonstrated that there was significant differences in the chemical composition between mouth-exhaled and nose-exhaled breath,which provided a theoretical basis for selection of exhalation mode.

Objective To establish a rapid screening method for 34 emerging contaminants in surface water by ultra-high performance liquid chromatography-quadrupole-time of flight mass spectrometry(UHPLC-Q-TOF-MS).Methods The pretreatment conditions of solid phase extraction(SPE)were op-timized by orthogonal experimental design and the surface water samples were concentrated and ex-tracted by Oasis? HLB and Oasis? MCX SPE columns in series.The extracts were separated by Kine-tex? EVO C18 column,with gradient elution of 0.1%formic acid aqueous solution and 0.1%formic acid methanol solution.Q-TOF-MS'fullscan'and'targeted MS/MS'modes were used to detect 34 emerging contaminants and to establish a database with 34 emerging contaminants precursor ion,prod-uct ion and retention times.Results The 34 emerging contaminants exhibited good linearity in the con-centration range respectively and the correlation coefficients(r)were higher than 0.97.The limit of de-tection was 0.2-10 ng/L and the recoveries were 81.2%-119.2%.The intra-day precision was 0.78%-18.70%.The method was applied to analyze multiple surface water samples and 6 emerging contaminants were detected,with a concentration range of 1.93-157.71 ng/L.Conclusion The method is simple and rapid for screening various emerging contaminants at the trace level in surface water.

With the rapid development of information technology， research on ancient TCM books has shifted from the traditional collation and digitization into intelligent knowledge service， thereby achieving the deep integration of ancient TCM books collation and clinical needs. Based on the clinical problem and knowledge element theory， we implemented in-depth indexing and knowledge mining for 600 kinds of ancient TCM books， built a knowledge sharing service platform for ancient TCM books by integrating database， cloud platform， knowledge graph and other technologies， and carried out the thematic literature research and developed databases for four major diseases including stroke， heart failure， liver cirrhosis， and diabetes. The digital intelligence products have been applied in hundreds of hospitals for evaluation and feedback. Finally， through "digital processing plus intelligent application"， the two-way interaction between ancient TCM books and current clinical practice is realized， and the path and paradigm of ancient TCM books knowledge serving the modern prevention and control of major diseases is formed， providing reference for the innovative utilization of ancient TCM books.

Xenotransplantation is an efficient pathway to solve the problem of transplant organ source deficiency in clinical settings. With the increasing progress of gene editing technique and immune suppression regimen, important development has been achieved on researches regarding pig to non-human primate kidney xenotransplantation, which provides a good condition for the introduction of the technique in the clinical application. In view of the substantial difference between human and non-human primate, and to meet the needs of current ethic requirements, it is necessary to perform subclinical studies for pig to human kidney xenotransplantation. In recent years, such subclinical studies with regard to the genetically modified pig to brain death recipient kidney xenotransplantation had been performed, indicating that kidney xenotransplantation gradually began to transit to the clinical development stage. However, donor/recipient selection and immune suppression regimen has not reached a consensus yet, and has to be clarified in subclinical studies. In this article, the current status and confronted problems of donor/recipient selection, immune suppression regimen and post transplantation management in the subclinical studies of kidney xenotransplantation were reviewed, aiming to promote the clinical transformation of kidney xenotransplantation to the clinical application.

Objective:To analyze the efficacy and safety of nalbuphine for analgesia in patients with non-mechanical ventilation in intensive care unit (ICU).Methods:From December 2018 to August 2021, a multicenter randomized controlled clinical study was conducted to select non-mechanical ventilation patients with analgesic needs admitted to ICU of four hospitals in Henan Province and Guizhou Province. Patients were randomly assigned to nalbuphine group and fentanyl group. The nalbuphine group was given continuous infusion of nalbuphine [0.05~0.20 mg/(kg·h)], and the fentanyl group was given continuous infusion of fentanyl [0.5~2.0 μg/(kg·h)]. The analgesic target was critical-care pain observation tool (CPOT) score<2. The observation time was 48 hours. The primary endpoint was CPOT score, the secondary endpoints were Richmond agitation-sedation score (RASS), ICU length of stay, adverse events, and proportion of mechanical ventilation. The quantitative data of the two groups were compared by t test or Mann-Whitney U test. The enumeration data were compared by chi square test or Fisher exact probability method. The data at different time points between groups were compared by repeated measures analysis of variance. Results:A total of 210 patients were enrolled, including 105 patients in the nalbuphine group and 105 patients in the fentanyl group. There was no significant difference in baseline data between the two groups (all P>0.05). There was no significant difference in CPOT score between nalbuphine group and fentanyl group at each time point after medication ( P>0.05), the CPOT score of both groups at each time point after medication was significantly lower than that before medication, and the analgesic target could be achieved and maintained 2 hours after medication. There was no significant difference in RASS between the two groups at each time point after medication ( P>0.05), which was significantly lower than that before medication, and the target sedative effect was achieved 2 hours after medication. There was no significant difference in ICU length of stay between nalbuphine group and fentanyl group [5.0(4.0,7.5) d vs. 5.0(4.0,8.0) d, P=0.504]. The incidence of delirium, nausea and vomiting, abdominal distension, pruritus, vertigo and other adverse events in the nalbuphine group was lower than that in the fentanyl group (all P<0.05). There was no significant difference in the incidence of other adverse events such as deep sedation, hypotension and bradycardia between the two groups (all P>0.05). The incidence of respiratory depression in nalbuphine group was not significantly different from that in fentanyl group ( P>0.05), but the proportion of mechanical ventilation was significantly lower than that in the fentanyl group [1.9% (2/105) vs. 8.6%(9/105), P=0.030]. Conclusions:Nalbuphine could be used for analgesia in ICU patients with non-mechanical ventilation. The target analgesic effect could be achieved within 2 hours, and it had a certain sedative effect with a low incidence of adverse reactions.