Aromatherapy refers to the method of using the aromatic components of plants in appropriate forms to act on the entire body or a specific area to prevent and treat diseases. Essential oils used in aromatherapy are hydrophobic liquids containing volatile aromatic molecules， such as limonene， linalool， linalool acetate， geraniol， and citronellol. These chemicals have been extensively studied and shown to have a variety of functions， including reducing anxiety， relieving depression， promoting sleep， and providing pain relief. Terpenoids are a class of organic molecules with relatively low lipid solubility. After being inhaled， they can pass through the nasal mucosa for transfer or penetrate the skin and enter the bloodstream upon local application. Some of these substances also have the ability to cross the blood-brain barrier， thereby exerting effects on the central nervous system. Currently， the academic community generally agrees that products such as essential oils and aromatherapy from aromatic plants have certain health benefits. However， the process of extracting a single component from it and successfully developing it into a drug still faces many challenges. Its safety and efficacy still need to be further verified through more rigorous and systematic experiments. This article systematically elaborated on the efficacy of aromatic substances， including plant extracts and natural small molecule compounds， in antibacterial and antiviral fields and the regulation of nervous system activity. As a result， a deeper understanding of aromatherapy was achieved. At the same time， the potential of these aromatic substances for drug development was thoroughly explored， providing important references and insights for possible future drug research and application.

[This corrects the article DOI: 10.1016/j.apsb.2019.01.013.].

Objective To investigate the expression levels of serum microRNA-21(miR-21)and microRNA-23a(miR-23a)in patients with Parkinson's disease(PD)and their correlations with cognitive function and inflammatory responses.Methods A total of 120 PD patients admitted to the Second Affiliated Hospital of Hebei North University between December 2019 and January 2022 were enrolled,along with 115 healthy controls from the same period.Serum miR-21 and miR-23a levels were measured by quantitative real-time PCR,while serum levels of IL-6,CRP,and TNF-α were determined by ELISA.According to Mini-Mental State Examination(MMSE)scores,PD patients were classified into a cognitive impairment group(MMSE<26,n=72)and a normal cognition group(MMSE≥26,n=48).General characteristics in clinical and biochemical indicators levels were compared between the two groups.Spearman correlation analysis was used to assess the relationships of miRNAs and MMSE scores.Multivariate logistic regression analysis was employed to identify risk factors for cognitive impairment.The predictive value of miR-21 and miR-23a was evaluated using Receiver Operating Characteristic(ROC)curve analysis.Results Serum miR-21,miR-23a,IL-6,CRP,and TNF-α levels were significantly higher in the PD group than in the control group(P<0.01).The cognitive impairment group showed higher levels of miR-21,miR-23a,and inflammatory factor than the cognitively normal group(P<0.01).Correlation analysis revealed that miR-21 and miR-23a levels were negatively correlated with MMSE scores(r=-0.472,-0.514;P<0.001)and positively correlated with IL-6,CRP,and TNF-α(P<0.001).Multivariate Logistic regression analysis revealed that high expression of miR-21,miR-23a,and a higher UPDRS score,were independent risk factors for cognitive impairment in PD patients(P<0.05).Combined detection of miR-21 and miR-23a showed higher predictive accuracy for cognitive impairment than either marker alone(P<0.05).Conclusion Serum expression levels of miR-21 and miR-23a was upregulated in PD patients,which were associated with cognitive function and inflammatory response.Combined detection shows good predictive value for cognitive impairment..

Objective: To investigate the potential therapeutic mechanisms of kaempferol , an active component in the traditional Chinese medicine gardenia , for lung cancer treatment using a network pharmacology approach . Methods: The main active ingredients and potential targets of Gardenia jasminoides were obtained through the Tra⁃ditional Chinese Medicine Pharmacology Database and Analysis Platform (TCMSP) , and combined with the lung cancer related target information collected from Gene Cards and OMIM databases , the intersection targets of Garde⁃nia jasminoides and lung cancer treatment were determined by drawing Venn diagrams . Further screening of core targets was conducted through PPI network analysis , and gene ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes ( KEGG) pathway enrichment analysis were performed using the Metascape platform . Auto dock software was used to evaluate the binding affinity between the active ingredients of Gardenia jasminoides and target proteins . In terms of experiments , cell proliferation ability was evaluated through CCK⁃8 assay , cell migration and invasion ability were detected through cell scratch healing assay and Transwell assay , and the expression levels of epithelial mesenchymal transition ( EMT) protein and inflammatory factors were detected by Western blot and RT⁃qPCR . Results: The active ingredient kaempferol in Gardenia jasminoides exhibited significant binding ability invasion of lung cancer cells . The results of Western blot and RT⁃qPCR further confirmed that kaempferol could promote an increase in E ⁃cadherin , a decrease in N ⁃cadherin and Vimentin , and reduce the expression of inflam⁃matory factors . Conclusion The active ingredient of Gardenia jasminoides , kaempferol , inhibits the proliferation ,migration and invasion of lung cancer cells by targeting BCL⁃2 , while reversing EMT progression and suppressing the expression levels of inflammatory cytokines in lung cancer cells , thus preventing lung cancer progression .

OBJECTIVE To analyze the compositional differences between Fructus Tritici Levis and Triticum aestivum， and to provide reference for identification and quality control of both. METHODS Twenty batches of Fructus Tritici Levis and three batches of T. aestivum were collected， and their fingerprints were acquired by high-performance liquid chromatography and the similarities were evaluated by the Evaluation System of Similarity of Chromatographic Fingerprints of Traditional Chinese Medicine （2012 version）. Cluster analysis （CA）， principal component analysis （PCA） and orthogonal partial least squares-discriminant analysis （OPLS-DA） were performed to analyze the difference of Fructus Tritici Levis and T. aestivum from different regions， and the differential components were screened. The contents of the six identified components in Fructus Tritici Levis and T. aestivum were determined. RESULTS The similarities of the fingerprints of Fructus Tritici Levis ranged from 0.928 to 0.996， and the relative similarities of T. aestivum with Fructus Tritici Levis ranged from 0.761 to 0.773. A total of 19 common peaks were calibrated， and six components including linolenic acid， linoleic acid， 5-heptadecylresorcinol， 5-nonadodecylresorcinol， 5- heneicosylresorcinol， and 5-tricosylresorcinol were identified. The results of CA and PCA showed that Fructus Tritici Levis and T. aestivum could be clearly distinguished； the distribution of Fructus Tritici Levis from Anhui province was relatively concentrated. The results of OPLS-DA showed that linolenic acid， linoleic acid， and other six unknown compounds were the differential components between Fructus Tritici Levis and T. aestivum. The average contents of the six identified components in Fructus Tritici Levis were 0.100 9， 1.094 0， 0.005 1， 0.030 9， 0.098 2，and 0.024 8 mg/g， respectively； the contents of linolenic acid and linoleic acid in Fructus Tritici Levis were significantly higher than those in T. aestivum （P＜0.05）.CONCLUSIONS The established qualitative and quantitative methods are simple and reliable， and can be used for the identification and quality evaluation of Fructus Tritici Levis and T. aestivum. The identified differential components， such as linolenic acid and linoleic acid， can also provide clues for the differentiation and pharmacological study of Fructus Tritici Levis and T. aestivum.

OBJECTIVE To analyze the compositional differences between Fructus Tritici Levis and Triticum aestivum， and to provide reference for identification and quality control of both. METHODS Twenty batches of Fructus Tritici Levis and three batches of T. aestivum were collected， and their fingerprints were acquired by high-performance liquid chromatography and the similarities were evaluated by the Evaluation System of Similarity of Chromatographic Fingerprints of Traditional Chinese Medicine （2012 version）. Cluster analysis （CA）， principal component analysis （PCA） and orthogonal partial least squares-discriminant analysis （OPLS-DA） were performed to analyze the difference of Fructus Tritici Levis and T. aestivum from different regions， and the differential components were screened. The contents of the six identified components in Fructus Tritici Levis and T. aestivum were determined. RESULTS The similarities of the fingerprints of Fructus Tritici Levis ranged from 0.928 to 0.996， and the relative similarities of T. aestivum with Fructus Tritici Levis ranged from 0.761 to 0.773. A total of 19 common peaks were calibrated， and six components including linolenic acid， linoleic acid， 5-heptadecylresorcinol， 5-nonadodecylresorcinol， 5- heneicosylresorcinol， and 5-tricosylresorcinol were identified. The results of CA and PCA showed that Fructus Tritici Levis and T. aestivum could be clearly distinguished； the distribution of Fructus Tritici Levis from Anhui province was relatively concentrated. The results of OPLS-DA showed that linolenic acid， linoleic acid， and other six unknown compounds were the differential components between Fructus Tritici Levis and T. aestivum. The average contents of the six identified components in Fructus Tritici Levis were 0.100 9， 1.094 0， 0.005 1， 0.030 9， 0.098 2，and 0.024 8 mg/g， respectively； the contents of linolenic acid and linoleic acid in Fructus Tritici Levis were significantly higher than those in T. aestivum （P＜0.05）.CONCLUSIONS The established qualitative and quantitative methods are simple and reliable， and can be used for the identification and quality evaluation of Fructus Tritici Levis and T. aestivum. The identified differential components， such as linolenic acid and linoleic acid， can also provide clues for the differentiation and pharmacological study of Fructus Tritici Levis and T. aestivum.

  Objective  To evaluate the severity and features of pelvic coronal plane tilt in individuals with adolescent idiopathic scoliosis (AIS) who had lumbar curvature during the gait cycle.  Methods  AIS patients with lumbar curvature and patients with microcurvature (Cobb Angle less than 10 degrees) treated in Peking Union Medical College Hospital from September 2020 to February 2023 were retrospectively included. According to PUMC conservative classification system and Spinal Full-length Standing X-ray, AIS patients with lumbar curvature were enrolled. The bilateral iliac crest was used as the bony marker of the pelvic coronal surface, and the bilateral iliac crest height and its changes were measured during the standing position and walking cycle, so as to evaluate the degree of pelvic coronal tilt in AIS patients with lumbar curvature.  Results  A total of 209 AIS patients with lumbar curvature and 36 patients with microcurvature who met the inclusion and exclusion criteria were enrolled. The proportion of AIS patients with lumbar curvature who had a "congruent" relationship between the higher iliac crest and the convex side of the spine in standing position (iliac crest lower on the convex side than on the concave side) was significantly higher in AIS patients with lumbar curvature than patients with microcurvature(58.9% vs. 30.6%, P=0.002). AIS patients with lumbar curvature had statistically different bilateral iliac crest height change values throughout the gait cycle (including minimum, maximum, swing phase minimum, and swing phase maximum) (all P < 0.001), and the iliac crest height change values on the convex side were significantly higher than those on the concave side (all P < 0.05), whereas the patients with microcurvature did not have any statistically significant bilateral iliac crest height change values throughout the gait cycle (all P > 0.05).  Conclusion  The height of the iliac crest on the convex side of the lumbar spine is lower than that on the concave side in the standing position of AIS patients with lumbar curvature, and the value of the change of the iliac crest on the convex side of the pelvis is greater than that on the concave side in walking to maintain the balance of the body, which may provide a new direction for the intervention in the clinical rehabilitation treatment of AIS patients with lumbar curvature.

OBJECTIVE: To investigate the clinical application of high-frequency color Doppler ultrasound (HFCDU) in detecting perforators in the deep adipose layers for harvesting super-thin anterolateral thigh flap (ALTF). METHODS: Between August 2019 and January 2023, 45 patients (46 sides) with skin and soft tissue defects in the foot and ankle were treated, including 29 males and 16 females, aged from 22 to 62 years, with an average of 46.7 years. The body mass index ranged from 19.6 to 36.2 kg/m ², with an average of 23.62 kg/m ². The causes of injury included traffic accident injury in 15 cases, heavy object crush injury in 20 cases, mechanical injury in 8 cases, heat crush injury in 1 case, and chronic infection in 1 case. There were 20 cases on the left side, 24 cases on the right side, and 1 case on both sides. After thorough debridement, the wound size ranged from 5 cm×4 cm to 17 cm×11 cm. All patients underwent free super-thin ALTF transplantation repair. HFCDU was used to detect the location of the perforators piercing the deep and superficial fascia, as well as the direction and branches of the perforators within the deep adipose layers before operation. According to the preoperative HFCDU findings, the dimensions of the super-thin ALTF ranged from 6 cm×4 cm to 18 cm×12 cm. The donor sites of the flaps were directly sutured. RESULTS: A total of 55 perforators were detected by HFCDU before operation, but 1 was not found during operation. During operation, a total of 56 perforators were found, and 2 perforators were not detected by HFCDU. The positive predictive value of HFCDU for identifying perforator vessels was 98.2%, and the sensitivity was 96.4%. Among the 54 perforators accurately located by HFCDU, the orientation of the perforators in the deep adipose layers was confirmed during operation. There were 21 perforators (38.9%) traveled laterally and inferiorly, 12 (22.2%) traveled medially and inferiorly, 14 (25.9%) traveled laterally and superiorly, 5 (9.3%) traveled medially and superiorly, and 2 (3.7%) ran almost vertically to the body surface. Among the 54 perforators accurately located by HFCDU, 35 were identified as type 1 perforators and 12 as type 2 perforators (HFCDU misidentified 7 type 2 perforators as type 1 perforators). The sensitivity of HFCDU in identifying type 1 perforators was 100%, with a positive predictive value of 83.3%. For type 2 perforators, the sensitivity was 63.2%, and the positive predictive value was 100%. The surgeries were successfully completed. The super-thin ALTF had a thickness ranging from 2 to 6 mm, with an average of 3.56 mm. All super-thin ALTF survived, however, 1 flap experienced a venous crisis at 1 day after operation, but it survived after emergency exploration and re-anastomosis of the veins; 1 flap developed venous crisis at 3 days after operation but survived after bleeding with several small incisions; 3 flaps had necrosis at the distal edge of the epidermis, which healed after undergoing dressing changes. All 45 patients were followed up 6-18 months (mean, 13.6 months). Three flaps required secondary defatting procedures, while the rest had the appropriate thickness, and the overall appearance was satisfactory. CONCLUSION Preoperative application of HFCDU to detect the perforator in the deep adipose layers can improve the success and safety of the procedure by facilitating the harvest of super-thin ALTF.
Male ; Female ; Humans ; Thigh/surgery* ; Plastic Surgery Procedures ; Prospective Studies ; Skin Transplantation ; Free Tissue Flaps ; Burns ; Soft Tissue Injuries/surgery* ; Ultrasonography, Doppler, Color ; Crush Injuries/surgery* ; Perforator Flap ; Treatment Outcome

Visceral leishmaniasis is a zoonotic parasitic disease caused by viscerotropic Leishmania species and transmitted by bites of infected phlebotomine sandflies, which is predominantly prevalent in the Indian subcontinent, eastern Africa and South America. Currently, visceral leishmaniasis is the second most fatal parasitic disease in the world. Because of climate changes, urban development and individual conditions, there are changes in the density of visceral leishmaniasis vector sandflies and the likelihood of contact with humans, resulting in a visceral leishmaniasis transmission risk. The review summarizes natural, social and biological factors affecting the transmission of visceral leishmaniasis, so as to provide insights into formulation of targeted control measures for visceral leishmaniasis.

BACKGROUND:Sepsis is one of the main causes of mortality in intensive care units(ICUs).Early prediction is critical for reducing injury.As approximately 36%of sepsis occur within 24 h after emergency department(ED)admission in Medical Information Mart for Intensive Care(MIMIC-IV),a prediction system for the ED triage stage would be helpful.Previous methods such as the quick Sequential Organ Failure Assessment(qSOFA)are more suitable for screening than for prediction in the ED,and we aimed to find a light-weight,convenient prediction method through machine learning. METHODS:We accessed the MIMIC-IV for sepsis patient data in the EDs.Our dataset comprised demographic information,vital signs,and synthetic features.Extreme Gradient Boosting(XGBoost)was used to predict the risk of developing sepsis within 24 h after ED admission.Additionally,SHapley Additive exPlanations(SHAP)was employed to provide a comprehensive interpretation of the model's results.Ten percent of the patients were randomly selected as the testing set,while the remaining patients were used for training with 10-fold cross-validation. RESULTS:For 10-fold cross-validation on 14,957 samples,we reached an accuracy of 84.1%±0.3%and an area under the receiver operating characteristic(ROC)curve of 0.92±0.02.The model achieved similar performance on the testing set of 1,662 patients.SHAP values showed that the five most important features were acuity,arrival transportation,age,shock index,and respiratory rate. CONCLUSION:Machine learning models such as XGBoost may be used for sepsis prediction using only a small amount of data conveniently collected in the ED triage stage.This may help reduce workload in the ED and warn medical workers against the risk of sepsis in advance.