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.

Immobilized enzyme-based enzyme electrode biosensors, characterized by high sensitivity and efficiency, strong specificity, and compact size, demonstrate broad application prospects in life science research, disease diagnosis and monitoring, etc. Immobilization of enzyme is a critical step in determining the performance (stability, sensitivity, and reproducibility) of the biosensors. Random immobilization (physical adsorption, covalent cross-linking, etc.) can easily bring about problems, such as decreased enzyme activity and relatively unstable immobilization. Whereas, directional immobilization utilizing amino acid residue mutation, affinity peptide fusion, or nucleotide-specific binding to restrict the orientation of the enzymes provides new possibilities to solve the problems caused by random immobilization. In this paper, the principles, advantages and disadvantages and the application progress of enzyme electrode biosensors of different directional immobilization strategies for enzyme molecular sensing elements by specific amino acids (lysine, histidine, cysteine, unnatural amino acid) with functional groups introduced based on site-specific mutation, affinity peptides (gold binding peptides, carbon binding peptides, carbohydrate binding domains) fused through genetic engineering, and specific binding between nucleotides and target enzymes (proteins) were reviewed, and the application fields, advantages and limitations of various immobilized enzyme interface characterization techniques were discussed, hoping to provide theoretical and technical guidance for the creation of high-performance enzyme sensing elements and the manufacture of enzyme electrode sensors.

Five saponins were isolated from the kernels of Momordica cochinchinensis, by macroporous resin, silica gel, ODS column chromatography, and semi preparative HPLC. Based on MS and NMR analysis, combining with alkaline hydrolysis and acid hydrolysis, their structures were identified as: gypsogenin-3-O-{β-D-galactopyranosyl (1→2)-[α-L-rhamnopyranosyl (1→3)]-β-D-glucuropyranonosyl}-28-O-β-D-xylopyranosyl (1→3)-[β-D-xylopyranosyl (1→4)]-α-L-rhamnopyranosyl (1→2)-β-D-fucopyranoside (1), quillaic acid-3-O-{β-D-galactopyranosyl (1→2)-[α-L-rhamnopyranosyl (1→3)]-β-D-glucuropyranonosyl}-28-O-β-D-xylopyranosyl (1→3)-[β-D-xylopyranosyl (1→4)]-α-L-rhamnopyranosyl (1→2)-β-D-fucopyranoside (2), gypsogenin-3-O-β-D-galactopyranosyl (1→2)-[α-L-rhamnopyranosyl (1→3)]-β-D-glucuropyranonoside sodium (3), quillaic acid-3-O-β-D-galactopyranosyl (1→2)-[α-L-rhamnopyranosyl (1→3)]-β-D-glucuropyranonoside sodium (4), 18α-quillaic acid-3-O-β-D-galactopyranosyl (1→2)-[α-L-rhamnopyranosyl (1→3)]-β-D-glucuropyranonoside (5). Compounds 1-5 were new compounds, and named as mubezhisides A, B, C, D, E, respectively. They all could obviously inhibited the growth of Candida albicans, C. parapsilosis, and C. tropicalis.

Biomolecular condensates are formed through phase separation of biomacromolecules such as proteins and RNAs. These condensates exhibit liquid-like properties that can futher transition into more stable material states. They form complex internal structures via multivalent weak interactions, enabling precise spatiotemporal regulations. However, the use of inconsistent and non-standardized terminology has become increasingly problematic, hindering academic exchange and the dissemination of scientific knowledge. Therefore, it is necessary to discuss the terminology related to biomolecular condensates in order to clarify concepts, promote interdisciplinary cooperation, enhance research efficiency, and support the healthy development of this field.

ObjectiveHepatocyte nuclear factor 4-alpha (HNF4A) is a critical transcription factor in the liver and pancreas. Dysfunctions of HNF4A lead to maturity onset diabetes of the young 1 (MODY1). Notably, MODY1 patients with HNF4A pathogenic mutations exhibit decreased responses to arginine and reduced plasma triglyceride levels, but the mechanisms remain unclear. This study aims to investigate the potential target genes transcriptionally regulated by HNF4A and explore its role in these metabolic pathways. MethodsA stable 293T cell line expressing the HNF1A reporter was overexpressed with HNF4A. RNA sequencing (RNA-seq) was performed to analyze transcriptional differences. Transcription factor binding site prediction was then conducted to identify HNF4A binding motifs in the promoter regions of relevant target genes. ResultsRNA-seq results revealed a significant upregulation of transmembrane 4 L six family member 5 (TM4SF5) mRNA in HNF4A-overexpressing cells. Transcription factor binding predictions suggested the presence of five potential HNF4A binding motifs in the TM4SF5 promoter. Finally, we confirmed that the DR1 site in the -57 to -48 region of the TM4SF5 promoter is the key binding motif for HNF4A. ConclusionThis study identified TM4SF5 as a target gene of HNF4A and determined the key binding motif involved in its regulation. Given the role of TM4SF5 as an arginine sensor in mTOR signaling activation and triglyceride secretion, which closely aligns with phenotypes observed in MODY1 patients, our findings provide novel insights into the possible mechanisms by which HNF4A regulates triglyceride secretion in the liver and arginine-stimulated insulin secretion in the pancreas.

Purpose: The aim of this study was to investigate the feasibility of an intelligent handheld ultrasound (US) device for assisting non-expert general practitioners (GPs) in detecting carotid plaques (CPs) in community populations. Methods: This prospective parallel controlled trial recruited 111 consecutive community residents. All of them underwent examinations by non-expert GPs and specialist doctors using handheld US devices (setting A, setting B, and setting C). The results of setting C with specialist doctors were considered the gold standard. Carotid intima-media thickness (CIMT) and the features of CPs were measured and recorded. The diagnostic performance of GPs in distinguishing CPs was evaluated using a receiver operating characteristic curve. Inter-observer agreement was compared using the intragroup correlation coefficient (ICC). Questionnaires were completed to evaluate clinical benefits. Results: Among the 111 community residents, 80, 96, and 112 CPs were detected in settings A, B, and C, respectively. Setting B exhibited better diagnostic performance than setting A for detecting CPs (area under the curve, 0.856 vs. 0.749; P<0.01). Setting B had better consistency with setting C than setting A in CIMT measurement and the assessment of CPs (ICC, 0.731 to 0.923). Moreover, measurements in setting B required less time than the other two settings (44.59 seconds vs. 108.87 seconds vs. 126.13 seconds, both P<0.01). Conclusion Using an intelligent handheld US device, GPs can perform CP screening and achieve a diagnostic capability comparable to that of specialist doctors.

Objective: Huntington’s disease (HD) is characterized by motor, cognitive, and neuropsychiatric symptoms. Oculomotor impairments and gait variability have been independently considered as potential markers in HD. However, an integrated analysis of eye movement and gait is lacking. We performed multiple examinations of eye movement and gait variability in HTT mutation carriers, analyzed the consistency between these parameters and clinical severity, and then examined the associations between oculomotor impairments and gait deficits. Methods: We included 7 patients with pre-HD, 30 patients with HD and 30 age-matched controls. We collected demographic data and assessed the Unified Huntington’s Disease Rating Scale (UHDRS) score. Examinations, including saccades, smooth pursuit tests, and optokinetic (OPK) tests, were performed to evaluate eye movement function. The parameters of gait include stride length, walking velocity, step deviation, step length, and gait phase. Results: HD patients have significant impairments in the latency and velocity of saccades, the gain of smooth pursuit, and the gain and slow phase velocities of OPK tests. Only the speed of saccades significantly differed between pre-HD patients and controls. There are significant impairments in stride length, walking velocity, step length, and gait phase in HD patients. The parameters of eye movement and gait variability in HD patients were consistent with the UHDRS scores. There were significant correlations between eye movement and gait parameters. Conclusion Our results show that eye movement and gait are impaired in HD patients and that the speed of saccades is impaired early in pre-HD. Eye movement and gait abnormalities in HD patients are significantly correlated with clinical disease severity.

Background/Aims: Metabolic dysfunction-associated steatohepatitis (MASH) is a significant risk factor for gallstone formation, but mechanisms underlying MASH-related gallstone formation remain unclear. Golgi membrane protein 1 (GOLM1) participates in hepatic cholesterol metabolism and is upregulated in MASH. Here, we aimed to explore the role of GOLM1 in MASH-related gallstone formation. Methods: The UK Biobank cohort was used for etiological analysis. GOLM1 knockout (GOLM1-/-) and wild-type (WT) mice were fed with a high-fat diet (HFD). Livers were excised for histology and immunohistochemistry analysis. Gallbladders were collected to calculate incidence of cholesterol gallstones (CGSs). Biles were collected for biliary lipid analysis. HepG2 cells were used to explore underlying mechanisms. Human liver samples were used for clinical validation. Results: MASH patients had a greater risk of cholelithiasis. All HFD-fed mice developed MASH, and the incidence of gallstones was 16.7% and 75.0% in GOLM1-/- and WT mice, respectively. GOLM1-/- decreased biliary cholesterol concentration and output. In vivo and in vitro assays confirmed that GOLM1 facilitated cholesterol efflux through upregulating ATP binding cassette transporter subfamily G member 5 (ABCG5). Mechanistically, GOLM1 translocated into nucleus to promote osteopontin (OPN) transcription, thus stimulating ABCG5-mediated cholesterol efflux. Moreover, GOLM1 was upregulated by interleukin-1β (IL-1β) in a dose-dependent manner. Finally, we confirmed that IL-1β, GOLM1, OPN, and ABCG5 were enhanced in livers of MASH patients with CGSs. Conclusions In MASH livers, upregulation of GOLM1 by IL-1β increases ABCG5-mediated cholesterol efflux in an OPN-dependent manner, promoting CGS formation. GOLM1 has the potential to be a molecular hub interconnecting MASH and CGSs.

Purpose: The aim of this study was to investigate the feasibility of an intelligent handheld ultrasound (US) device for assisting non-expert general practitioners (GPs) in detecting carotid plaques (CPs) in community populations. Methods: This prospective parallel controlled trial recruited 111 consecutive community residents. All of them underwent examinations by non-expert GPs and specialist doctors using handheld US devices (setting A, setting B, and setting C). The results of setting C with specialist doctors were considered the gold standard. Carotid intima-media thickness (CIMT) and the features of CPs were measured and recorded. The diagnostic performance of GPs in distinguishing CPs was evaluated using a receiver operating characteristic curve. Inter-observer agreement was compared using the intragroup correlation coefficient (ICC). Questionnaires were completed to evaluate clinical benefits. Results: Among the 111 community residents, 80, 96, and 112 CPs were detected in settings A, B, and C, respectively. Setting B exhibited better diagnostic performance than setting A for detecting CPs (area under the curve, 0.856 vs. 0.749; P<0.01). Setting B had better consistency with setting C than setting A in CIMT measurement and the assessment of CPs (ICC, 0.731 to 0.923). Moreover, measurements in setting B required less time than the other two settings (44.59 seconds vs. 108.87 seconds vs. 126.13 seconds, both P<0.01). Conclusion Using an intelligent handheld US device, GPs can perform CP screening and achieve a diagnostic capability comparable to that of specialist doctors.

Purpose: The aim of this study was to investigate the feasibility of an intelligent handheld ultrasound (US) device for assisting non-expert general practitioners (GPs) in detecting carotid plaques (CPs) in community populations. Methods: This prospective parallel controlled trial recruited 111 consecutive community residents. All of them underwent examinations by non-expert GPs and specialist doctors using handheld US devices (setting A, setting B, and setting C). The results of setting C with specialist doctors were considered the gold standard. Carotid intima-media thickness (CIMT) and the features of CPs were measured and recorded. The diagnostic performance of GPs in distinguishing CPs was evaluated using a receiver operating characteristic curve. Inter-observer agreement was compared using the intragroup correlation coefficient (ICC). Questionnaires were completed to evaluate clinical benefits. Results: Among the 111 community residents, 80, 96, and 112 CPs were detected in settings A, B, and C, respectively. Setting B exhibited better diagnostic performance than setting A for detecting CPs (area under the curve, 0.856 vs. 0.749; P<0.01). Setting B had better consistency with setting C than setting A in CIMT measurement and the assessment of CPs (ICC, 0.731 to 0.923). Moreover, measurements in setting B required less time than the other two settings (44.59 seconds vs. 108.87 seconds vs. 126.13 seconds, both P<0.01). Conclusion Using an intelligent handheld US device, GPs can perform CP screening and achieve a diagnostic capability comparable to that of specialist doctors.