Rapid and non-destructive identification of Panax ginseng origins using hyperspectral imaging, visible light imaging, and X-ray imaging combined with multi-source data fusion strategies.

The geographical origin of Panax ginseng significantly influences its nutritional value and chemical composition, which in turn affects its market price. Traditional methods for analyzing these differences are often time-consuming and require substantial quantities of reagents, rendering them inefficient. Therefore, hyperspectral imaging (HSI) in conjunction with X-ray technology were used for the swift and non-destructive traceability of Panax ginseng origin. Initially, outlier samples were effectively rejected by employing a combined isolated forest algorithm and density peak clustering (DPC) algorithm. Subsequently, random forest (RF) and support vector machine (SVM) classification models were constructed using hyperspectral spectral data. These models were further optimized through the application of 72 preprocessing methods and their combinations. Additionally, to enhance the model's performance, four variable screening algorithms were employed: SelectKBest, genetic algorithm (GA), least absolute shrinkage and selection operator (LASSO), and permutation feature importance (PFI). The optimized model, utilizing second derivative, auto scaling, permutation feature importance, and support vector machine (2nd Der-AS-PFI-SVM), achieved a prediction accuracy of 93.4 %, a Kappa value of 0.876, a Brier score of 0.030, an F1 score of 0.932, and an AUC of 0.994 on an independent prediction set. Moreover, the image data (including color information and texture information) extracted from color and X-ray images were used to construct classification models and evaluate their performance. Among them, the SVM model constructed using texture information from X -ray images performed the best, and it achieved a prediction accuracy of 63.0 % on the validation set, with a Brier score of 0.181, an F1 score of 0.518, and an AUC of 0.553. By implementing mid-level fusion and high-level data fusion based on the Stacking strategy, it was found that the model employing a high-level fusion of hyperspectral spectral information and X-ray images texture information significantly outperformed the model using only hyperspectral spectral information. This advanced model attained a prediction accuracy of 95.2 %, a Kappa value of 0.912, a Brier score of 0.027, an F1 score of 0.952, and an AUC of 0.997 on the independent prediction set. In summary, this study not only provides a novel technical path for fast and non-destructive traceability of Panax ginseng origin, but also demonstrates the great potential of the combined application of HSI and X-ray technology in the field of traceability of both medicinal and food products.

A base editor for the long-term restoration of auditory function in mice with recessive profound deafness.

A prevalent recessive mutation (c.2485C>T, p.Q829X) within the OTOF gene leads to profound prelingual hearing loss. Here we show that in Otof mice harbouring a mutation (c.2482C>T, p.Q828X) homozygous to human OTOF that faithfully mimics the hearing-loss phenotype, a base editor (consisting of the deaminase ABE7.10max and the Cas9 variant SpCas9-NG) packaged in adeno-associated viruses and injected into the inner ear of the mice via the round-window membrane effectively corrected the pathogenic mutation, with no apparent off-target effects. The treatment restored the levels of the otoferlin protein in 88% of the inner hair cells and stably rescued the auditory function of the mice to near-wild-type levels for over 1.5 years while improving synaptic exocytosis in the inner hair cells. We also show that an adenine base editor that targets the prevalent human OTOF mutation restored hearing in humanized mice to levels comparable to those of the wild-type counterparts. Base editors may be effective for the treatment of hereditary deafness.

CDC20 Holds Novel Regulation Mechanism in RPA1 during Different Stages of DNA Damage to Induce Radio-Chemoresistance.

Targeting CDC20 can enhance the radiosensitivity of tumor cells, but the function and mechanism of CDC20 on DNA damage repair response remains vague. To examine that issue, tumor cell lines, including KYSE200, KYSE450, and HCT116, were utilized to detect the expression, function, and underlying mechanism of CDC20 in radio-chemoresistance. Western blot and immunofluorescence staining were employed to confirm CDC20 expression and location, and radiation could upregulate the expression of CDC20 in the cell nucleus. The homologous recombination (HR) and non-homologous end joining (NHEJ) reporter gene systems were utilized to explore the impact of CDC20 on DNA damage repair, indicating that CDC20 could promote HR repair and radio/chemo-resistance. In the early stages of DNA damage, CDC20 stabilizes the RPA1 protein through protein-protein interactions, activating the ATR-mediated signaling cascade, thereby aiding in genomic repair. In the later stages, CDC20 assists in the subsequent steps of damage repair by the ubiquitin-mediated degradation of RPA1. CCK-8 and colony formation assay were used to detect the function of CDC20 in cell vitality and proliferation, and targeting CDC20 can exacerbate the increase in DNA damage levels caused by cisplatin or etoposide. A tumor xenograft model was conducted in BALB/c-nu/nu mice to confirm the function of CDC20 in vivo, confirming the in vitro results. In conclusion, this study provides further validation of the potential clinical significance of CDC20 as a strategy to overcome radio-chemoresistance via uncovering a novel role of CDC20 in regulating RPA1 during DNA damage repair.

Enhancing hepatocellular carcinoma management: prognostic value of integrated CCL17, CCR4, CD73, and HHLA2 expression analysis.

PURPOSE: Hepatocellular carcinoma (HCC) is a critical global health concern, with existing treatments benefiting only a minority of patients. Recent findings implicate the chemokine ligand 17 (CCL17) and its receptor CCR4 as pivotal players in the tumor microenvironment (TME) of various cancers. This investigation aims to delineate the roles of CCL17 and CCR4 in modulating the tumor's immune landscape, assessing their potential as therapeutic interventions and prognostic markers in HCC. METHODS: 873 HCC patients post-radical surgery from 2008 to 2012 at Zhongshan Hospital, Fudan University were retrospectively examined. These individuals were stratified into a training cohort (n = 354) and a validation cohort (n = 519). Through immunohistochemical analysis on HCC tissue arrays, the expressions of CCL17, CCR4, CD73, CD47, HHLA2, and PD-L1 were quantified. Survival metrics were analyzed using the Cox model, and a prognostic nomogram was devised via R software. RESULTS: The investigation confirmed the presence of CCL17 and CCR4 within the cancerous and stromal compartments of HCC tissues, associating their heightened expression with adverse clinical markers and survival outcomes. Notably, the interplay between CD73 and CCR4 expression in tumor stroma highlighted a novel cellular entity, CCR4 + CD73 + stromal cells, impacting overall and relapse-free survival. A prognostic nomogram amalgamating these immunological markers and clinical variables was established, offering refined prognostic insights and aiding in the management of HCC. The findings suggest that reduced CCR4 and CCR4 + CD73 + cell prevalence may forecast improved outcomes post-TACE. CONCLUSION: This comprehensive evaluation of CCR4, CCL17, and associated markers introduces a nuanced understanding of the HCC immunological milieu, proposing CCR4 + CD73 + stromal cells as critical to HCC pathogenesis and patient stratification.

Differential involvement of cAMP/PKA-, PLC/PKC- and Ca2+/calmodulin-dependent pathways in GnRH-induced prolactin secretion and gene expression in grass carp pituitary cells.

Gonadotropin-releasing hormone (GnRH) is a key stimulator for gonadotropin secretion in the pituitary and its pivotal role in reproduction is well conserved in vertebrates. In fish models, GnRH can also induce prolactin (PRL) release, but little is known for the corresponding effect on PRL gene expression as well as the post-receptor signalling involved. Using grass carp as a model, the functional role of GnRH and its underlying signal transduction for PRL regulation were examined at the pituitary level. Using laser capture microdissection coupled with RT-PCR, GnRH receptor expression could be located in carp lactotrophs. In primary cell culture prepared from grass carp pituitaries, the native forms of GnRH, GnRH2 and GnRH3, as well as the GnRH agonist [D-Arg6, Pro9, NEt]-sGnRH were all effective in elevating PRL secretion, PRL mRNA level, PRL cell content and total production. In pituitary cells prepared from the rostral pars distalis, the region in the carp pituitary enriched with lactotrophs, GnRH not only increased cAMP synthesis with parallel CREB phosphorylation and nuclear translocation but also induced a rapid rise in cytosolic Ca2+ by Ca2+ influx via L-type voltage-sensitive Ca2+ channel (VSCC) with subsequent CaM expression and NFAT2 dephosphorylation. In carp pituitary cells prepared from whole pituitaries, GnRH-induced PRL secretion was reduced/negated by inhibiting cAMP/PKA, PLC/PKC and Ca2+/CaM/CaMK-II pathways but not the signalling events via IP3 and CaN/NFAT. The corresponding effect on PRL mRNA expression, however, was blocked by inhibiting cAMP/PKA/CREB/CBP and Ca2+/CaM/CaN/NFAT2 signalling but not PLC/IP3/PKC pathway. At the pituitary cell level, activation of cAMP/PKA pathway could also induce CaM expression and Ca2+ influx via VSCC with parallel rises in PRL release and gene expression in a Ca2+/CaM-dependent manner. These findings, as a whole, suggest that the cAMP/PKA-, PLC/PKC- and Ca2+/CaM-dependent cascades are differentially involved in GnRH-induced PRL secretion and PRL transcript expression in carp lactotrophs. During the process, a functional crosstalk between the cAMP/PKA- and Ca2+/CaM-dependent pathways may occur with PRL release linked with CaMK-II and PKC activation and PRL gene transcription caused by nuclear action of CREB/CBP and CaN/NFAT2 signalling.

Inhibiting the Aggregation of Aß by Natural Product Molecules.

The abnormal aggregation of Aß has been considered one of the primary causative factors for Alzheimer's disease. Diverse molecular entities have been developed to mitigate the formation of toxic Aß aggregates within the brain by inhibiting Aß aggregation. Recognizing that many FDA-approved drugs are derived from natural products, we present a summary of recent discoveries involving natural product molecules with inhibitory effects on Aß aggregation. By consolidating these findings, our review offers researchers a concise overview of the latest advancements in natural product-based interventions for Alzheimer's disease.

Development and validation of a prediction model for postoperative pneumonia in patients who received spinal surgery: A retrospective study.

Objectives: To develop and validate a risk prediction model by identifying the preoperative factors associated with an increased risk of pneumonia after spinal surgery. Methods: This study included patients with spinal disease from two hospitals between January 2021 and June 2023. The patients were divided into the training and validation sets, which were categorized as postoperative pneumonia (POP) or non-POP, respectively. This study identified the independent risk variables for POP using a multivariate logistic regression analysis. A nomogram prediction model was developed and validated using risk factors, receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) to assess predictive performance. Results: Following exclusion, 2223 patients from Changzheng Hospital were enrolled in the training set and 357 patients from the No. 905 Hospital of PLA Navy were enrolled in the validation set. Univariate and multivariate logistic regression analyses revealed that operation time, American Society of Anesthesiologists (ASA) grade, smoking, non-wearing of medical masks, lack of preoperative respiratory training, chronic obstructive pulmonary disease (COPD), underlying diseases, and spinal section were risk factors for POP development in patients with spinal diseases. The area under the ROC curve of the training set was 0.950, whereas that of the validation set was 0.879. The model calibration curves demonstrated good agreement, and the DCA indicated a high expected net benefit value. Conclusion: The POP risk prediction model has high accuracy and efficiency in predicting POP in patients with spinal diseases. POP development is influenced by factors such as operation length, ASA grade, smoking, non-wearing of medical masks, lack of preoperative respiratory training, COPD, underlying diseases, and lumbar surgery.

Advancing illicit connection diagnosis of urban stormwater pipes: Comprehensive analysis with EEM fluorescence spectroscopy.

Urban drainage systems are significant contributors to the issue of black-odorous water bodies. The current application of stormwater pipe inspection technologies faces substantial limitations, especially in industrial areas with diverse wastewater. This study introduced an innovative approach using excitation-emission matrix (EEM) fluorescence spectroscopy for rapid and accurate diagnosis, providing a new perspective for diagnosing illicit connections. In single wastewater-type areas like residential zones, the method achieved a remarkable 91.5 % accuracy solely through spectra observation and fluorescence peak intensity comparison, outperforming conventional NH3-N-based techniques, which reached an accuracy of only 68.1 %. For regions with complex wastewater scenarios, after EEM subtraction, the residual spectra can be roughly categorized into four distinctive categories based on characteristics. This provides a preliminary assessment and helps in initially identifying the types and sources of inflowing wastewater. Furthermore, the least squares (LS) method refines diagnosis results, offering calculated coefficients reflecting the probability and severity of suspected wastewater intrusion. Simulation experiments and field sample analyses validated the feasibility and accuracy of the EEM-based method, highlighting its advantages for diagnosing illicit connections in both single and mixed wastewater scenarios. The results can significantly narrow down the investigation scope and enhance the confirmation of wastewater sources, exhibiting promising application prospects.

Unraveling the enigma: A comprehensive review of solid pseudopapillary tumor of the pancreas.

Solid pseudopapillary tumor of the pancreas (SPTP) is a rare neoplasm predominantly observed in young females. Pathologically, CTNNB1 mutations, ß-catenin nuclear accumulation, and subsequent Wnt-signaling pathway activation are the leading molecular features. Accurate preoperative diagnosis often relies on imaging techniques and endoscopic biopsies. Surgical resection remains the mainstay treatment. Risk models, such as the Fudan Prognostic Index, show promise as predictive tools for assessing the prognosis of SPTP. Establishing three types of metachronous liver metastasis can be beneficial in tailoring individualized treatment and follow-up strategies. Despite advancements, challenges persist in understanding its etiology, establishing standardized treatments for unresectable or metastatic diseases, and developing a widely recognized grading system. This comprehensive review aims to elucidate the enigma by consolidating current knowledge on the epidemiology, clinical presentation, pathology, molecular characteristics, diagnostic methods, treatment options, and prognostic factors.

Prediction of Effectiveness and Toxicities of Immune Checkpoint Inhibitors Using Real-World Patient Data.

PURPOSE: Although immune checkpoint inhibitors (ICIs) have improved outcomes in certain patients with cancer, they can also cause life-threatening immunotoxicities. Predicting immunotoxicity risks alongside response could provide a personalized risk-benefit profile, inform therapeutic decision making, and improve clinical trial cohort selection. We aimed to build a machine learning (ML) framework using routine electronic health record (EHR) data to predict hepatitis, colitis, pneumonitis, and 1-year overall survival. METHODS: Real-world EHR data of more than 2,200 patients treated with ICI through December 31, 2018, were used to develop predictive models. Using a prediction time point of ICI initiation, a 1-year prediction time window was applied to create binary labels for the four outcomes for each patient. Feature engineering involved aggregating laboratory measurements over appropriate time windows (60-365 days). Patients were randomly partitioned into training (80%) and test (20%) sets. Random forest classifiers were developed using a rigorous model development framework. RESULTS: The patient cohort had a median age of 63 years and was 61.8% male. Patients predominantly had melanoma (37.8%), lung cancer (27.3%), or genitourinary cancer (16.4%). They were treated with PD-1 (60.4%), PD-L1 (9.0%), and CTLA-4 (19.7%) ICIs. Our models demonstrate reasonably strong performance, with AUCs of 0.739, 0.729, 0.755, and 0.752 for the pneumonitis, hepatitis, colitis, and 1-year overall survival models, respectively. Each model relies on an outcome-specific feature set, though some features are shared among models. CONCLUSION: To our knowledge, this is the first ML solution that assesses individual ICI risk-benefit profiles based predominantly on routine structured EHR data. As such, use of our ML solution will not require additional data collection or documentation in the clinic.

SN2 Reaction at the Amide Nitrogen Center Enables Hydrazide Synthesis.

Nucleophilic substitutions are fundamentally important transformations in synthetic organic chemistry. Despite the substantial advances in bimolecular nucleophilic substitutions (SN2) at saturated carbon centers, analogous SN2 reaction at the amide nitrogen atom remains extremely limited. Here we report an SN2 substitution method at the amide nitrogen atom with amine nucleophiles for nitrogen-nitrogen (N-N) bond formation that leads to a novel strategy toward biologically and medicinally important hydrazide derivatives. We found the use of sulfonate-leaving groups at the amide nitrogen atom played a pivotal role in the reaction. This new N-N coupling reaction allows the use of O-tosyl hydroxamates as electrophiles and readily available amines, including acyclic aliphatic amines and saturated N-heterocycles as nucleophiles. The reaction features mild conditions, broad substrate scope (>80 examples), excellent functional group tolerability, and scalability. The method is applicable to late-stage modification of various approved drug molecules, thus enabling complex hydrazide scaffold synthesis.

The formation and control of disinfection by-products by two-step chlorination for sewage effluent: Role of organic chloramine decomposition among molecular weight fractions.

With the increasing discharge of wastewater effluent to natural waters, there is an urgent need to achieve both pathogenic microorganism inactivation and the mitigation of disinfection by-products (DBPs) during disinfection. Studies have shown that two-step chlorination, which injected chlorine disinfectant by splitting into two portions, was more effective in inactivating Escherichia coli than one-step chlorination under same total chlorine consumption and contact time. In this study, we observed a substantial reduction in the formation of five classes of CX3R-type DBPs, especially highly toxic haloacetonitriles (HANs), during two-step chlorination of secondary effluent when the mass ratio of chlorine-to-nitrogen exceeded 2. The shift of different chlorine species (free chlorine, monochloramine and organic chloramine) verified the decomposition of organic chloramines into monochloramine during second chlorination stage. Notably, the organic chloramines generated from the low molecular weight (< 1 kDa) fraction of dissolved organic nitrogen in effluent organic matter tended to decompose during the second step chlorination leading to the mitigation of HAN formation. Furthermore, the microbiological analysis showed that two-step chlorinated effluent had a slightly lower ecological impact on surface water compared to one-step chlorination. This work provided more information about the two-step chlorination for secondary effluent, especially in terms of organic chloramine transformation and HAN control.

The insightful water quality analysis and predictive model establishment via machine learning in dual-source drinking water distribution system.

Dual-source drinking water distribution systems (DWDS) over single-source water supply systems are becoming more practical in providing water for megacities. However, the more complex water supply problems are also generated, especially at the hydraulic junction. Herein, we have sampled for a one-year and analyzed the water quality at the hydraulic junction of a dual-source DWDS. The results show that visible changes in drinking water quality, including turbidity, pH, UV254, DOC, residual chlorine, and trihalomethanes (TMHs), are observed at the sample point between 10 and 12 km to one drinking water plant. The average concentration of residual chlorine decreases from 0.74 ± 0.05 mg/L to 0.31 ± 0.11 mg/L during the water supplied from 0 to 10 km and then increases to 0.75 ± 0.05 mg/L at the end of 22 km. Whereas the THMs shows an opposite trend, the concentration reaches to a peak level at hydraulic junction area (10-12 km). According to parallel factor (PARAFAC) and high-performance size-exclusion chromatography (HPSEC) analysis, organic matters vary significantly during water distribution, and tryptophan-like substances and amino acids are closely related to the level of THMs. The hydraulic junction area is confirmed to be located at 10-12 km based on the water quality variation. Furthermore, data-driven models are established by machine learning (ML) with test R2 higher than 0.8 for THMs prediction. And the SHAP analysis explains the model results and identifies the positive (water temperature and water supply distance) and negative (residual chlorine and pH) key factors influencing the THMs formation. This study conducts a deep understanding of water quality at the hydraulic junction areas and establishes predictive models for THMs formation in dual-sources DWDS.

A rare case of intervertebral disc calcification combined with ossification of the posterior longitudinal ligament in a child: a case report and literature review.

BACKGROUND: Intervertebral disc calcification (IDC) combined with calcification in children has been sporadically reported, while ossification of the posterior longitudinal ligament (OPLL) in the cervical spine in pediatric patients is exceedingly rare. The aim of this study is to investigate the potential prognosis and outcomes associated with this condition. CASE PRESENTATION: We present an unusual case involving a 10-year-old Chinese child diagnosed with calcified cervical disc herniation and ossification of the posterior longitudinal ligament. Conservative treatment measures were implemented, and at the 1-month and 6-month follow-up, the patient's pain exhibited significant improvement. Subsequent cervical MRI and CT scans revealed the complete disappearance of OPLL and substantial absorption of the calcified disc. During the three-month follow-up, CT demonstrated slight residual disc calcification, however, the patient remained asymptomatic with no discernible limitation in cervical motion. CONCLUSIONS: We conducted a comprehensive review of several cases presenting with the same diagnosis. It is noteworthy that IDC combined with OPLL in children constitutes a rare clinical entity. Despite imaging indications of potential spinal canal occupation, the majority of such cases demonstrate complete absorption following conservative treatment, with OPLL exhibiting a faster absorption rate than calcified discs.

Rapid characterization of physical properties for the pharmaceutical pellet cores based on NIR spectroscopy and ensemble learning.

During the development of sustained-release pellets, the physical characteristics of the pellet cores can affect drug release in the preparation. The method based on near-infrared (NIR) spectroscopy and ensemble learning was proposed to swiftly assess the physical properties of the pellet cores. In the research, the potential of three algorithms, direct standardization (DS), partial least squares regression (PLSR) and generalized regression neural network (GRNN), was investigated and compared. The performance of the DS, PLSR and GRNN models were improved after applying bootstrap aggregating (Bagging) ensemble learning. And the Bagging-GRNN model showed the best predictive capacity. Except for inter-particle porosity, the mean absolute deviations of other 11 physical parameters were less than 1.0. Furthermore, the cosine coefficient values between the actual and predicted physical fingerprints was higher than 0.98 for 15 out of the 16 validation samples when using the Bagging-GRNN model. To reduce the model complexity, the 60 variables significantly correlated with angle of repose, particle size (D50) and roundness were utilized to develop the simplified Bagging-GRNN model. And the simplified model showed satisfactory predictive capacity. In summary, the developed ensemble modelling strategy based NIR spectra is a promising approach to rapidly characterize the physical properties of the pellet cores.

Traditional Herb (Moxa) Modified Zinc Oxide Nanosheets for Quick, Efficient and High Tissue Penetration Therapy of Fungal Infection.

Fungal infection possesses the characteristics of high invasion depth and easy formation of a biofilm under the skin, which greatly hinders the treatment process. Here, traditional Chinese medicine moxa is carbonized and modified with zinc oxide (ZnO) nanosheets to synthesize carbonized moxa@ZnO (CMZ) with the dual response properties of yellow light (YL) and ultrasound (US) for synergistic antifungal therapy. CMZ with narrow bandgap can respond to long-wavelength YL that is highly safe and helpful for skin repair. Simultaneously, CMZ with a piezoelectric effect can further enhance the photocatalytic efficiency under the stimulation of US with high tissue penetration. Gene mechanism investigation indicates that when exposed to US and YL irradiation, CMZ-based therapy can adjust the expression of genes associated with fungal virulence, metabolic activity, mycelial growth and biofilm development, thus efficaciously eradicating planktonic Candida albicans (C. albicans) and mature biofilm. Importantly, despite the 1.00 cm thick tissue barrier, CMZ can rapidly eliminate 99.9% of C. albicans within 4 min, showing a satisfactory deep fungicidal efficacy. The in vivo therapeutic effect of this strategy is demonstrated in both open wound and deep cutaneous infection tests, speaking of dramatically better efficacy than the traditional fungicide ketoconazole (KTZ).

Recent Progress in Site-Selective Modification of Peptides and Proteins Using Macrocycles.

Peptides and proteins undergo crucial modifications to alter their physicochemical properties to expand their applications in diverse fields. Various techniques, such as unnatural amino acid incorporation, enzyme catalysis, and chemoselective methods, have been employed for site-selective peptide and protein modification. While traditional methods remain valuable, advancement in host-guest chemistry introduces innovative and promising approaches for the selective modification of peptides and proteins. Macrocycles exhibit robust binding affinities, particularly with natural amino acids, which facilitates their use in selectively binding to specific sequences. This distinctive property endows macrocycles with the potential for modification of target peptides and proteins. This review provides a comprehensive overview of strategies utilizing macrocycles for the selective modification of peptides and proteins. These strategies unlock new possibilities for constructing antibody-drug conjugates and stabilizing volatile medications.

Tracking the source of antibiotic resistome in the stormwater network drainage in the presence of sewage illicit connections.

Stormwater pipes are illicitly connected with sewage in many countries, which means that sewage enters stormwater pipes and the drainage is discharged to surface water without any treatment. Sewage contains more pathogens and highly risky antibiotic resistance genes (ARGs) than surface runoff. Therefore, sewage may alter the microbial and ARG compositions in stormwater pipe drainage, which in turn leads to an increased risk of resistance in surface water. However, the effects of sewage on ARGs in the drainage of stormwater networks have not been systematically studied. This study characterized the microbial and ARG composition of several environmental compartments of a typical stormwater network and quantified their contributions to those in the drainage. This network transported ARGs and microorganisms from sewage, sediments in stormwater pipes, and surface runoff into the drainage and thus into the river. According to metagenomic analysis, multidrug resistance genes were most abundant in all samples and the numbers and relative abundance of ARGs in the drainage collected during wet weather were comparable to that of sewage. The results of SourceTracker showed that the relative contribution of sewage was double that of rainwater and surface runoff in the drainage during wet weather for both microorganisms and ARGs. Desulfovibrio, Azoarcus, and Sulfuritalea were connected with the greatest number of ARGs and were most abundant in the sediments of stormwater pipes. Furthermore, stochastic processes were found to dominate ARG and microbial assembly, as the effects of high hydrodynamic intensity outweighed the effects of environmental filtration and species interactions. The findings of this study can increase our understanding of ARGs in stormwater pipe drainage, a crucial medium linking ARGs in sewage to environmental ARGs.

Research progress of posttraumatic stress disorder / 重庆医学

Posttraumatic stress disorder(PTSD)is a delayed and persistent mental disorder caused by severe psychological trauma,and the prevalence of PTSD is gradually increasing.This article summarizes the epidemiology,causes and pathogenesis,diagnosis,treatment,future and prospect of PTSD,in order to provide reference for the prevention,diagnosis and treatment of PTSD.