Plasma metabolites and inflammatory proteins profiling predict outcome of Fufang Duzhong Jiangu granules treating Kashin-Beck disease.

To investigate predictive biomarkers that could be used to identify patients' response to treatment, plasma metabolomics and proteomics analyses were performed in Kashin-Beck disease (KBD) patients treated with Fufang Duzhong Jiangu Granules (FDJG). Plasma was collected from 12 KBD patients before treatment and 1 month after FDJG treatment. LC-MS and olink proteomics were employed for obtaining plasma metabolomics profiling and inflammatory protein profiles. Patients were classified into responders and non-responders based on drug efficacy. Enrichment analyses of differential metabolites and proteins of the responders at baseline and after treatment were conducted to study the mechanism of drug action. Differential metabolites and proteins between the two groups were screened as biomarkers to predict the drug efficacy. The receiver operating characteristic curve was used to evaluate the prediction accuracy of biomarkers. The changes in metabolites and inflammatory proteins in responders after treatment reflected the mechanism of FDJG treatment for KBD, which may act on glycerophospholipid metabolism, d-glutamine and d-glutamate metabolism, nitrogen metabolism and NF-kappa B signaling pathway. Three metabolites were identified as potential predictors: N-undecanoylglycine, ß-aminopropionitrile and PC [18:3(6Z,9Z,12Z)/20:4(8Z,11Z,14Z,17Z)]. For inflammatory protein, interleukin-8 was identified as a predictive biomarker to detect responders. Combined use of these four biomarkers had high predictive ability (area under the curve = 0.972).

Safe Disposal of Accident Wastewater in Chemical Industrial Parks Using Non-Thermal Plasma with ZnO-Fe3O4 Composites.

Chemical wastewater has a high concentration of toxic and hazardous antibiotic pollutants, which not only devastates the ecological environment and disrupts the ecological balance, but also endangers human health. This research proposed a non-thermal plasma (NTP) combined with a ZnO-Fe3O4 nano-catalyst system to achieve the efficient degradation of ciprofloxacin (CIP) in chemical wastewater. Firstly, ZnO-Fe3O4 composite materials were prepared using hydrothermal method and characterized with scanning electron microscopy (SEM), transmission electron microscope (TEM), X-ray diffractometer (XRD), X-ray photoelectron spectroscopy (XPS), etc. With the sole NTP, NTP/ZnO, and NTP/ZnO-Fe3O4 systems, the removal efficiency of CIP can reach 80.1%, 88.2%, and 99.6%, respectively. The optimal doping amount of Fe3O4 is 14%. Secondly, the capture agent experiment verified that ·OH, ·O2-, and 1O2 all have a certain effect on CIP degradation. Then, liquid chromatography-mass spectrometry (LC-MS) was used to detect the intermediate and speculate its degradation pathway, which mainly included hydroxyl addition, hydroxyl substitution, and piperazine ring destruction. After treatment with the NTP/ZnO-Fe3O4 system, the overall toxicity of the product was reduced. Finally, a cyclic experiment was conducted, and it was found that the prepared ZnO-Fe3O4 catalyst has good reusability. The NTP/ZnO-Fe3O4 was also applied in practical pharmaceutical wastewater treatment and has practical applicability.

Identification and Verification of Hub Mitochondrial Dysfunction Genes in Osteoarthritis Based on Bioinformatics Analysis.

Objective: Age-related mitochondrial dysfunction and associated oxidative stress may contribute to the development of osteoarthritis. The aim of this study was to identify hub genes associated with mitochondrial dysfunction in osteoarthritis (OA) patients, helping predict the risk of OA, and revealing the mechanism of OA progression. Methods: OA expression data and mitochondrial dysfunction genes were downloaded from GEO (GSE55235, GSE82107, and GSE114007) and GeneCard databases. The differentially expressed mitochondrial dysfunction genes (DEMDFGs) between OA and control samples were screened. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes pathways were analyzed for DEMDFGs. The hub genes were determined by WGCNA and LASSO regression analysis. ROC curves manifested the diagnostic efficacy of each hub gene. A nomogram model was constructed and validated to predict OA risk. The expression of hub genes in OA and normal chondrocytes was verified by external datasets, qRT-PCR and western blotting. Results: A total of 31 DEMDFGs were identified, with 15 genes upregulated and 16 genes downregulated. GO functional enrichment analysis revealed that DEMDFGs were enriched in biological processes related to energy metabolism and cellular respiration. By employing weighted gene coexpression network analysis, we identified four distinct coexpression modules, among which the blue module exhibited the strongest correlation with OA. The intersection between DEMDFGs and this module yielded eight candidate genes. After LASSO analysis of the data, four hub genes (ACADL, CYBA, SLC19A2, and UCP2) were identified as potential biomarkers for OA. The expression levels of these four genes were externally validated in the GSE114007 dataset. And the biologically differential expression of these four genes has been verified in OA and normal chondrocytes. Moreover, the four hub genes had good sensitivity and specificity by ROC curve analysis, and the risk model constructed with these four genes showed promising performance. In conclusion, our study may provide novel mitochondrial dysfunction hub genes with potential clinical applications for understanding the pathology, diagnosis, and treatment of OA.

Decoding the enigma: unveiling the molecular transmission of avian-associated tet(X4)-positive E. coli in Sichuan Province, China.

Tigecycline is considered one of the "last resort antibiotics" for treating complex infections caused by multidrug-resistant (MDR) bacteria, especially for combating clinical resistant strains that produce carbapenemases. However, the tet(X4) gene, which carried by different plasmids can mediate high levels of bacterial resistance to tigecycline, was first reported in 2019. Here, we report the emergence of the plasmid-mediated tet(X4) in avian environment of Sichuan Province. A total of 21 tet(X4)-positive Escherichia coli (E. coli) strains were isolated and identified from avian samples in selected regions, with an isolation rate of 1.6% (21/1,286), and all of them were MDR strains. Multilocus Sequence Typing (MLST) method was used to classify the 21 tet(X4)-positive E. coli into the ST206, ST761, ST155, ST1638, ST542, and ST767 types, which also belong to the 3 phylogenetic subgroups A, B1, and C. Tet(X4) is located on mobile plasmids that can be efficiently and stably propagated. The results of fitness cost experiments showed that tet(X4)-positive plasmids may incur some fitness cost to host bacteria, but different tet(X4)-positive plasmids bring about differential fitness costs. Whole-genome sequencing further confirmed the tet(X4) gene can be located on IncX1-type plasmids and the core genetic structures are ISVsa3-rdmc-tet(X4) or rdmc-tet(X4)-ISVsa3, the former is a 7 copies tandem repeat structure. In this study, we isolated and identified tet(X4)-positive E. coli from the avian origin in Sichuan, analyzed the mobility of the tet(X4) by conjugational transfer and S1-PFGE, and evaluated the biological characteristics of the tet(X4)-positive plasmid using the results of conjugational frequency, plasmid stability, and fitness costs. Finally, combined with the third-generation whole-genome sequencing analysis, the molecular transmission characteristics of the tet(X4) were preliminarily clarified, providing a scientific basis for guiding veterinary clinical use in this area, as well as risk assessment and prevention of the transfer and spread of tigecycline resistant strains or genes.

Pathogenesis, Animal Models, and Drug Discovery of Alzheimer's Disease.

Alzheimer's disease (AD), the most common cause of dementia, is a chronic neurodegenerative disease induced by multiple factors. The high incidence and the aging of the global population make it a growing global health concern with huge implications for individuals and society. The clinical manifestations are progressive cognitive dysfunction and lack of behavioral ability, which not only seriously affect the health and quality of life of the elderly, but also bring a heavy burden to the family and society. Unfortunately, almost all the drugs targeting the classical pathogenesis have not achieved satisfactory clinical effects in the past two decades. Therefore, the present review provides more novel ideas on the complex pathophysiological mechanisms of AD, including classical pathogenesis and a variety of possible pathogenesis that have been proposed in recent years. It will be helpful to find out the key target and the effect pathway of potential drugs and mechanisms for the prevention and treatment of AD. In addition, the common animal models in AD research are outlined and we examine their prospect for the future. Finally, Phase I, II, III, and IV randomized clinical trials or on the market of drugs for AD treatment were searched in online databases (Drug Bank Online 5.0, the U.S. National Library of Medicine, and Alzforum). Therefore, this review may also provide useful information in the research and development of new AD-based drugs.

Changes in the cortical network during sleep stage transitions.

Sleep state transitions are closely related to insomnia, drowsiness, and sleep maintenance. However, how the cortical network varies during such a transition process remains unclear. Changes in the cortical interaction during the short-term process of sleep stage transitions were investigated. In all, 40 healthy young participants underwent overnight polysomnography. The phase transfer entropy of six frequency bands was obtained from 16 electroencephalography channels to assess the strength and direction of information flow between the cortical regions. Differences in the cortical network between the first and the last 10 s in a 40-s transition period across wakefulness, N1, N2, N3, and rapid eye movement were, respectively, studied. Various frequency bands exhibited different patterns during the sleep stage transitions. It was found that the mutual transitions between the sleep stages were not necessarily the opposite. More significant changes were observed in the sleep deepening process than in the process of sleep awakening. During sleep stage transitions, changes in the inflow and outflow strength of various cortical regions led to regional differences, but for the entire sleep progress, such an imbalance did not intensify, and a dynamic balance was instead observed. The detailed findings of variations in cortical interactions during sleep stage transition promote understanding of sleep mechanism, sleep process, and sleep function. Additionally, it is expected to provide helpful clues for sleep improvement, like reducing the time required to fall asleep and maintaining sleep depth.

Research progress on metabolomics in the quality evaluation and clinical study of Panax ginseng.

Panax ginseng, an essential component of traditional medicine and often referred to as the king of herbs, has played a pivotal role in medicine globally for several millennia. Previously, traditional phytochemical methods were mainly used for quality evaluation and pharmacological mechanism studies of ginseng, resulting in the lack of systematicness and innovation and hindering the development and utilization of ginseng resources. Since the beginning of the new century, systems biology technology represented by metabolomics has shown unique advantages in the modernization and internationalization of herbal medicine, establishing a bridge for communication between traditional medicine and modern medicine. P. ginseng, a special herb used in medicine and food, is one of the main research objects for qualitative and quantitative analysis of metabolomics and has gradually become the focus of researchers globally. Here, we conducted a comprehensive summary and analysis of numerous studies published in ginseng metabolomics. This review aims to provide more novel ideas for the quality evaluation, development, and clinical application of ginseng in the future and offer more useful technical references for the modernization and internationalization of herbal medicine based on metabolomics.

Dissemination and prevalence of plasmid-mediated high-level tigecycline resistance gene tet (X4).

With the large-scale use of antibiotics, antibiotic resistant bacteria (ARB) continue to rise, and antibiotic resistance genes (ARGs) are regarded as emerging environmental pollutants. The new tetracycline-class antibiotic, tigecycline is the last resort for treating multidrug-resistant (MDR) bacteria. Plasmid-mediated horizontal transfer enables the sharing of genetic information among different bacteria. The tigecycline resistance gene tet(X) threatens the efficacy of tigecycline, and the adjacent ISCR2 or IS26 are often detected upstream and downstream of the tet(X) gene, which may play a crucial driving role in the transmission of the tet(X) gene. Since the first discovery of the plasmid-mediated high-level tigecycline resistance gene tet(X4) in China in 2019, the tet(X) genes, especially tet(X4), have been reported within various reservoirs worldwide, such as ducks, geese, migratory birds, chickens, pigs, cattle, aquatic animals, agricultural field, meat, and humans. Further, our current researches also mentioned viruses as novel environmental reservoirs of antibiotic resistance, which will probably become a focus of studying the transmission of ARGs. Overall, this article mainly aims to discuss the current status of plasmid-mediated transmission of different tet(X) genes, in particular tet(X4), as environmental pollutants, which will risk to public health for the "One Health" concept.

Minimal EEG channel selection for depression detection with connectivity features during sleep.

BACKGROUND AND OBJECTIVES: Sleeping cortical electroencephalogram (EEG) has the potential for depression detection, for different sleep structure and cortical connection have been proved in depressed patients. However, the operation of multi-channel sleep EEG recording is cumbersome and requires laboratory equipment and professional sleep technician. Here, we focus on the depression detection using minimal sleep EEG channels. METHODS: Sixteen channels of EEG data of 30 patients with depression and 30 age-matched normal controls were recorded during sleep. Power spectral density of each single EEG channel was calculated, followed by measuring the symbolic transfer entropy (STE) and weighed phase lag index (WPLI) between EEG channel pairs in various frequency bands. Thereafter, these features were evaluated by F-score in the two-way classification (depression vs. control) of 30-s sleep EEG segments. Based on the F-score, entropy method was introduced to calculate the weight which could further assess the classification ability of various EEG channels or channel pairs. Finally, machine learning was implemented to verify the important EEG channels or channel pairs in depression diagnosis. RESULTS: The features characterizing the inter-hemispheric connectivity in the posterior lobe, especially in the temporal lobe, showed high classification capacity. The classification accuracy of using two and four EEG channels in the temporal lobe were 97.96% and 99.61%, respectively. CONCLUSIONS: This study showed the possibility of using only a few sleep EEG channels for depression screening, which may greatly facilitate the diagnosis of depression outside the hospital.

Graph Theory Analysis of the Cortical Functional Network During Sleep in Patients With Depression.

Depression, a common mental illness that seriously affects the psychological health of patients, is also thought to be associated with abnormal brain functional connectivity. This study aimed to explore the differences in the sleep-state functional network topology in depressed patients. A total of 25 healthy participants and 26 depressed patients underwent overnight 16-channel electroencephalography (EEG) examination. The cortical networks were constructed by using functional connectivity metrics of participants based on the weighted phase lag index (WPLI) between the EEG signals. The results indicated that depressed patients exhibited higher global efficiency and node strength than healthy participants. Furthermore, the depressed group indicated right-lateralization in the δ band. The top 30% of connectivity in both groups were shown in undirected connectivity graphs, revealing the distinct link patterns between the depressed and control groups. Links between the hemispheres were noted in the patient group, while the links in the control group were only observed within each hemisphere, and there were many long-range links inside the hemisphere. The altered sleep-state functional network topology in depressed patients may provide clues for a better understanding of the depression pathology. Overall, functional network topology may become a powerful tool for the diagnosis of depression.

One-stage efficacy of single tract minimally invasive ECIRS in the improved prone frog split-leg position for staghorn stones.

OBJECTIVE: To explore the feasibility, safety, and effectiveness of single tract minimally invasive endoscopic combined intrarenal surgery (stmECIRS) in the improved prone frog split-leg position for staghorn stones. METHOD: A total of 83 patients with staghorn stones were retrospectively reviewed between January 2018 and June 2021. According to surgical procedure and position, patients were divided into a group of single tract minimally invasive percutaneous nephroscopy (stmPNL) in the prone position and a group of stmECIRS in the improved prone frog split-leg position (turned to the prone position after preset the flexible ureteroscope sheath in lithotomy position, meanwhile, bend both hips and knees to be frog abduction). Demographic characteristics, laboratory tests, stone characters, surgical information, stone-free rate (SFR), and perioperative complications were observed and analyzed. RESULTS: There were no significant differences in demographic characteristics, changes level of Scr and Hb, stone size, radiation density, length of hospital stay, and operation time between the two groups. One-stage SFR in the stmECIRS group was significantly higher than that in the stmPNL group (84.4% vs. 57.9%) (P = 0.007), only 2 patients required blood transfusion after surgery (P = 0.862), and other postoperative complications were not statistically significant (P = 0.345). CONCLUSIONS: StmECIRS in improved prone frog split-leg position has a higher one-stage SFR than stmPNL for staghorn renal stones, and without complications increased, which is a safe, efficient and feasible treatment.

Characterization of specific spatial functional connectivity difference in depression during sleep.

Depression is a common mental illness and a large number of researchers have been still devoted to exploring effective biomarkers for the identification of depression. Few researches have been conducted on functional connectivity (FC) during sleep in depression. In this paper, a novel depression characterization is proposed using specific spatial FC features of sleep electroencephalography (EEG). Overnight polysomnography recordings were obtained from 26 healthy individuals and 25 patients with depression. The weighted phase lag indexes (WPLIs) of four frequency bands and five sleep periods were obtained from 16 EEG channels. The high discriminative connections extracted via feature evaluation and the cross-within variation (CW)-the spatial feature constructed to characterize the different performances in inter- and intra-hemispheric FC based on WPLIs, were utilized to classify patients and normal controls. The results showed that enhanced average FC and spatial differences, higher inter-hemispheric FC and lower intra-hemispheric FC, were found in patients. Furthermore, abnormalities in the inter-hemispheric connections of the temporal lobe in the theta band should be important indicators of depression. Finally, both CW and high discriminative WPLI features performed well in depression screening and CW was more specific for characterizing abnormal cortical EEG performance of depression. Our work investigated and characterized the abnormalities in sleep cortical activity in patients with depression, and may provide potential biomarkers for assisting with depression identification and new insights into the understanding of pathological mechanisms in depression.

Regional characterization of functional connectivity in patients with sleep apnea hypopnea syndrome during sleep.

Objective. Sleep apnea hypopnea syndrome (SAHS) induces abnormalities in brain function. This study aims to find features that can characterize the impact of SAHS on the brain functional connectivity (FC) during sleep.Approach. Seventy-eight participants (39 SAHS patients and 39 age-matched healthy controls) were recruited and underwent a whole night of polysomnography. The improved weighted phase lag index algorithm was utilized to evaluate FC inδ,θ,α,ß, andγbands of six EEG channels. The regional FC features were further constructed to characterize the asymmetries of FC between the left and right hemispheres, the imbalances of FC between the inter- and intra-hemispheres, and those between the anterior and posterior cortex, respectively. Then, support vector machines and feature evaluation were used to verify the discriminative ability for the abnormal FC in SAHS patients of the above-mentioned features.Main results.The study observed abnormal FC changes in SAHS patients during sleep in multiple frequency bands. Moreover, regional FC features performed better in SAHS screening, and important features were mainly distributed inßandγbands.Significance. Our research exhibited the abnormal regional FC in SAHS patients during sleep, which provided new insights and established indicators to investigate the changes of brain function in patients.

Characterization of the abnormal cortical effective connectivity in patients with sleep apnea hypopnea syndrome during sleep.

BACKGROUND AND OBJECTIVES: Sleep apnea hypopnea syndrome (SAHS) is a prevalent sleep breathing disorder that can lead to brain damage and is also a risk factor for cognitive impairment and some common diseases. Studies on cortical effective connectivity (EC) during sleep may provide more direct and pathological information and shed new light on brain dysfunction due to SAHS. However, the EC is rarely explored in SAHS patients, especially during different sleep stages. METHODS: To this end, six-channel EEG signals of 43 SAHS patients and 41 healthy participants were recorded by whole-night polysomnography (PSG). The symbolic transfer entropy (STE) was applied to measure the EC between cortical regions in different frequency bands. Posterior-anterior ratio (PA) was employed to evaluate the posterior-to-anterior pattern of information flow based on overall cortical EC. The statistical characteristics of the STE and PA and of the intra-individual normalized parameters (STE* and PA*) were served as different feature sets for classifying the severity of SAHS. RESULTS: Although the patterns of STE across electrodes were similar, significant differences were found between the patient and the control groups. The variation trends across stages in the PA were also different in multiple frequency bands between groups. Important features extracted from the STE* and PA* were distributed in multiple rhythms, mainly in δ, α, and γ. The PA* feature set gave the best results, with accuracies of 98.8% and 83.3% for SAHS diagnosis (binary) and severity classification (four-way). CONCLUSIONS: These results suggest that modifications in cortical EC were existed in SAHS patients during sleep, which may help characterize cortical abnormality in patients.

A PET imaging study of the brain changes of glucose metabolism in patients with temporal lobe epilepsy and depressive disorder.

BACKGROUND: This study aims to compare the difference of the brain changes of glucose metabolism between temporal lobe epilepsy patients (TLE) with major depressive disorder and temporal TLE without major depressive disorder. METHODS: A total of 24 TLE patients, who met the inclusion criteria of our hospital, were enrolled in this study. They were divided into a TLE with depression group (n = 11) and a TLE without depression group (n = 13), according to the results of the HAMD-24 Scale. Two groups patients were examined using 18F-FDG PET brain imaging. RESULTS: The low metabolic regions of the TLE with depression group were mainly found in the left frontal lobe, temporal lobe and fusiform gyrus, while the high metabolic regions of the TLE with depression group were mainly located in the right frontal lobe, visual joint cortex and superior posterior cingulate cortex. Both of the TLE groups had high metabolic compensation in the non-epileptic area during the interictal period. CONCLUSIONS: There is an uptake difference of 18F-FDG between TLE patients with depression and TLE patients without depression in multiple encephalic regions.

Application of Fourier transform near-infrared spectroscopy combined with GC in rapid and simultaneous determination of essential components in Amomum villosum.

A method is described using rapid and sensitive Fourier transform near-infrared spectroscopy combined with Gas Chromatograpy internal standard method detection for the simultaneous identification and determination of three bioactive compounds in Amomum villosum samples. Partial least squares regression is selected as the analysis type and multiplicative scatter correction, second derivative, and SNV were adopted for the spectral pretreatment. The correlation coefficients (R) of the calibration models were above 0.95 and the root mean square error of predictions were under 0.8. The developed models were applied to unknown samples with satisfantory results. The established method was validated and can be applied to the intrinsic quality control of Amomum villosum.

Sleep-Dependent Anomalous Cortical Information Interaction in Patients With Depression.

Depression is a prevalent mental illness with high morbidity and is considered the main cause of disability worldwide. Brain activity while sleeping is reported to be affected by such mental illness. To explore the change of cortical information flow during sleep in depressed patients, a delay symbolic phase transfer entropy of scalp electroencephalography signals was used to measure effective connectivity between cortical regions in various frequency bands and sleep stages. The patient group and the control group shared similar patterns of information flow between channels during sleep. Obvious information flows to the left hemisphere and to the anterior cortex were found. Moreover, the occiput tended to be the information driver, whereas the frontal regions played the role of the receiver, and the right hemispheric regions showed a stronger information drive than the left ones. Compared with healthy controls, such directional tendencies in information flow and the definiteness of role division in cortical regions were both weakened in patients in most frequency bands and sleep stages, but the beta band during the N1 stage was an exception. The computable sleep-dependent cortical interaction may provide clues to characterize cortical abnormalities in depressed patients and should be helpful for the diagnosis of depression.

Sleep-Dependent Directional Interactions of the Central Nervous System-Cardiorespiratory Network.

OBJECTIVE: We investigated the nature of interactions between the central nervous system (CNS) and the cardiorespiratory system during sleep. METHODS: Overnight polysomnography recordings were obtained from 33 healthy individuals. The relative spectral powers of five frequency bands, three ECG morphological features and respiratory rate were obtained from six EEG channels, ECG, and oronasal airflow, respectively. The synchronous feature series were interpolated to 1 Hz to retain the high time-resolution required to detect rapid physiological variations. CNS-cardiorespiratory interaction networks were built for each EEG channel and a directionality analysis was conducted using multivariate transfer entropy. Finally, the difference in interaction between Deep, Light, and REM sleep (DS, LS, and REM) was studied. RESULTS: Bidirectional interactions existed in central-cardiorespiratory networks, and the dominant direction was from the cardiorespiratory system to the brain during all sleep stages. Sleep stages had evident influence on these interactions, with the strength of information transfer from heart rate and respiration rate to the brain gradually increasing with the sequence of REM, LS, and DS. Furthermore, the occipital lobe appeared to receive the most input from the cardiorespiratory system during LS. Finally, different ECG morphological features were found to be involved with various central-cardiac and cardiac-respiratory interactions. CONCLUSION: These findings reveal detailed information regarding CNS-cardiorespiratory interactions during sleep and provide new insights into understanding of sleep control mechanisms. SIGNIFICANCE: Our approach may facilitate the investigation of the pathological cardiorespiratory complications of sleep disorders.

Early-Onset Schizophrenia Showed Similar but More Severe Olfactory Identification Impairment Than Adult-Onset Schizophrenia.

BACKGROUND: "Early-onset schizophrenia" (EOS) is defined as disease with onset before the age of 18 years. This subset of schizophrenia exhibits worse cognitive function and carries a worse prognosis than adult-onset schizophrenia (AOS). Olfactory impairment has been found in patients with schizophrenia-spectrum disorders. However, most research has focused on olfactory impairment in patients with AOS: olfactory function in EOS is not known. The aim of this study was to investigate the olfactory identification ability in EOS, and its relationship with negative symptoms. METHODS: We compared olfactory function between two independent samples: 40 patients with EOS and 40 age- and sex-matched healthy controls (HCs); as well as 40 patients with AOS and 40 age- and sex-matched HCs. The University of Pennsylvania Smell Identification Test was administered. RESULTS: The EOS group and AOS group exhibited worse olfactory identification ability than HCs; impairment correlated significantly with negative symptoms. Olfactory identification was worse in patients suffering EOS compared with those suffering AOS. CONCLUSION: Olfactory identification impairment may be a trait marker of schizophrenia.

Chemosensory Anhedonia in Patients With Schizophrenia and Individuals With Schizotypy: A Questionnaire Study.

Anhedonia, the loss or decline of the ability to enjoy pleasure, is an important clinical characteristic of schizophrenia. Schizotypal traits refer to the appearance of subclinical symptoms of schizophrenia across normal people. Still, few studies have investigated chemosensory anhedonia in schizophrenia patients and schizotypy individuals. Seventy-one schizophrenia patients (SCZ), 162 schizotypy individuals (SCT) as selected by the Schizotypal Personality Questionnaire (SPQ), and 182 healthy controls (HC) participated in our study. We used the Positive and Negative Syndrome Scale (PANSS) to measure the clinical symptoms of schizophrenia patients. All participants completed the Chemosensory Pleasure Scale (CPS), which was used to assess participants' smell and taste hedonic capacities. We found that the three groups differed in chemosensory anhedonia. The SCZ group presented more severe chemosensory anhedonia than the SCT group, and the SCT group presented more severe chemosensory anhedonia than the HC group. We also found that chemosensory hedonic capacity was negatively correlated with negative schizotypal traits in the SCT group. Our results suggested that chemosensory anhedonia is an important characteristic of schizophrenia spectrum disorders.