As an exclusive Miao medicine of Honwing Pharma （Guizhou） Co. Ltd.， Yifei Zhike capsules are both a prescription drug and an over-the-counter （OTC） drug. Its main ingredients include Ranunculus ternatus and Panax notoginseng. With the effects of nourishing Yin and moistening the lungs， as well as relieving cough and reducing phlegm， Yifei Zhike capsules are often used in the treatment of acute and chronic bronchitis， pulmonary tuberculosis， and other diseases. However， there is insufficient understanding of their efficacy， suitable syndromes， and safety in clinical practice， with a lack of relevant expert consensus on clinical application. To standardize their clinical application， 30 experts from the fields of respiratory medicine， pharmacy， and evidence-based medicine were invited to develop an Expert Consensus on the Clinical Application of Yifei Zhike Capsules （Consensus for short） through evidence-based medicine methods. The Consensus clarified the syndrome characteristics， disease stages， dosages， treatment courses， combined medication， and other norms in the treatment of acute/chronic bronchitis and pulmonary tuberculosis and could be applicable to clinical physicians and pharmacists in medical and health institutions at all levels. In disease diagnosis， it provided diagnostic criteria for traditional Chinese medicine and Western medicine and clarified that the suitable traditional Chinese medicine syndrome was the syndrome of Qi-Yin deficiency with intermingled phlegm-blood stasis. Clinical studies have confirmed that Yifei Zhike capsules combined with standard anti-tuberculosis therapy can effectively improve the symptoms of pulmonary tuberculosis patients， increase the sputum smear conversion rate， and promote the absorption of lesions. When treating acute cough caused by respiratory tract infections， Yifei Zhike capsules can increase the markedly effective rate and the seven-day disappearance rate of cough symptoms. Meanwhile， recommendations for specific usage， dosages， and treatment courses were given for different diseases， and it was pointed out that long-term medication required key monitoring of adverse reactions. In safety， the adverse reactions of Yifei Zhike capsules involved multiple aspects such as the digestive system and allergic reactions， and pregnant women and women during menstruation were prohibited from using it. In addition， modern research has shown that Yifei Zhike capsules have an adjuvant therapeutic effect on tuberculous pleurisy and may be effective for inflammatory and benign pulmonary nodules. However， further research should be conducted on the toxicological safety of long-term medication. The formulation of the Consensus provides a scientific basis for the rational clinical application of Yifei Zhike capsules， which helps to improve clinical efficacy and reduce medication risks.

As an exclusive Miao medicine of Honwing Pharma （Guizhou） Co. Ltd.， Yifei Zhike capsules are both a prescription drug and an over-the-counter （OTC） drug. Its main ingredients include Ranunculus ternatus and Panax notoginseng. With the effects of nourishing Yin and moistening the lungs， as well as relieving cough and reducing phlegm， Yifei Zhike capsules are often used in the treatment of acute and chronic bronchitis， pulmonary tuberculosis， and other diseases. However， there is insufficient understanding of their efficacy， suitable syndromes， and safety in clinical practice， with a lack of relevant expert consensus on clinical application. To standardize their clinical application， 30 experts from the fields of respiratory medicine， pharmacy， and evidence-based medicine were invited to develop an Expert Consensus on the Clinical Application of Yifei Zhike Capsules （Consensus for short） through evidence-based medicine methods. The Consensus clarified the syndrome characteristics， disease stages， dosages， treatment courses， combined medication， and other norms in the treatment of acute/chronic bronchitis and pulmonary tuberculosis and could be applicable to clinical physicians and pharmacists in medical and health institutions at all levels. In disease diagnosis， it provided diagnostic criteria for traditional Chinese medicine and Western medicine and clarified that the suitable traditional Chinese medicine syndrome was the syndrome of Qi-Yin deficiency with intermingled phlegm-blood stasis. Clinical studies have confirmed that Yifei Zhike capsules combined with standard anti-tuberculosis therapy can effectively improve the symptoms of pulmonary tuberculosis patients， increase the sputum smear conversion rate， and promote the absorption of lesions. When treating acute cough caused by respiratory tract infections， Yifei Zhike capsules can increase the markedly effective rate and the seven-day disappearance rate of cough symptoms. Meanwhile， recommendations for specific usage， dosages， and treatment courses were given for different diseases， and it was pointed out that long-term medication required key monitoring of adverse reactions. In safety， the adverse reactions of Yifei Zhike capsules involved multiple aspects such as the digestive system and allergic reactions， and pregnant women and women during menstruation were prohibited from using it. In addition， modern research has shown that Yifei Zhike capsules have an adjuvant therapeutic effect on tuberculous pleurisy and may be effective for inflammatory and benign pulmonary nodules. However， further research should be conducted on the toxicological safety of long-term medication. The formulation of the Consensus provides a scientific basis for the rational clinical application of Yifei Zhike capsules， which helps to improve clinical efficacy and reduce medication risks.

The compilation instructions for the Expert Consensus on Clinical Application of Yifei Zhike Capsules systematically expound the development background， methodological framework， and core achievements of this consensus. In view of the problems existing in the clinical application of Yifei Zhike Capsules， such as insufficient efficacy evidence and lack of standardized syndrome differentiation， the Institute of Basic Research in Clinical Medicine， China Academy of Chinese Medical Sciences took the lead and collaborated with 21 tertiary grade-A hospitals and research institutions across China to form a multidisciplinary expert group （comprising 30 experts in clinical medicine， pharmacy， and methodology）. The compilation work was carried out in strict accordance with the World Health Organization （WHO） guidelines， the GB/T 1.1-2020 standard， and the writing specifications for the explanatory notes of expert consensus on clinical application of Chinese patent medicines. Through systematic literature retrieval （including 32 studies， with 24 clinical studies）， Grading of Recommendations Assessment， Development and Evaluations （GRADE）-based evidence grading， and multiple rounds of discussions using the nominal group method （25 experts voted to determine 17 clinical questions）， 5 evidence-based recommendations and 11 expert consensus suggestions were formed. It is clarified that this medicine （Yifei Zhike Capsules） is applicable to the treatment of expectoration/hemoptysis in acute and chronic bronchitis and the adjuvant treatment of pulmonary tuberculosis. It is recommended that it can be used alone or in combination with anti-tuberculosis drugs. The safety evaluation shows that this medicine mainly induces the following adverse reactions： mild gastrointestinal reactions （such as nausea and abdominal pain） and rashes. The contraindicated populations include pregnant women and women during menstruation. The compilation process of the consensus underwent three rounds of expert letter reviews， two rounds of peer reviews， and quality control assessments to ensure methodological rigor and clinical applicability. In addition， through policy alignment， academic promotion， and a dynamic revision mechanism， the standardization of clinical application was promoted， providing a demonstration for the evidence-based transformation of characteristic therapies of Miao medicine.

ObjectiveTo develop traditional Chinese medicine （TCM） formulae for the treatment of nonsevere coronavirus disease 2019 （COVID-19） and to explore its anti-inflammatory mechanism. MethodsThe dysregulated signaling pathways were determined in macrophages from bronchoalveolar lavage fluid of COVID-19 patients and in lung epithelial cells infected with SARS-CoV-2 in vitro based on transcriptome analysis. A total of 102 TCM formulae for the clinical treatment of nonsevere COVID-19 were collected through literature. The pathway-reversing rates of these formulae in macrophages and lung epithelial cells were evaluated based on signature signaling pathways， and the basic formula was determined in conjunction with TCM theory. The commonly used Chinese materia medica for nonsevere COVID-19 were summarized from the 102 TCM formulae as abovementioned. And together with the screening results from the Pharmacopoeia of the People's Republic of China， a “Chinese materia medica pool” was esta-blished for the development of TCM formulae for COVID-19. The regulatory effects of each herb on signaling pathways were obtained based on targeted transcriptome analysis. Oriented at reversing dysregulated signaling pathways of COVID-19， the calculation was carried out， and the artificial intelligent methods for compositing formulae， that are exhaustive method and parallel computing， were used to obtain candidate compound formulas. Finally， with reference to professional experience， an innovative formula for the treatment of nonsevere COVID-19 was developed. The ethanol extract of the formula was evaluated for its anti-inflammatory effects by detecting the mRNA expression of interleukin 1b （Il1b）， C-X-C motif chemokine ligand 2 （Cxcl2）， C-X-C motif chemokine ligand 10 （Cxcl10）， C-C motif chemokine ligand 2 （Ccl2）， nitric oxide synthase 2 （Nos2）， and prostaglandin-endoperoxide synthase 2 （Ptgs2） using reverse transcription-quantitative polymerase chain reaction （RT-qPCR） in RAW264.7 cells treated with lipopolysaccharide （LPS）. ResultsIn macrophages and lung epithelial cells， 34 dysregulated signaling pathways associated with COVID-19 were identified respectively. The effects of the 102 formulae for clinical treatment of nonsevere COVID-19 were evaluated based on the dysregulated signaling pathways and targeted transcriptome， and the result showed that Yinqiao Powder and Pingwei Powder （银翘散合平胃散， YQPWP） ranked first， reversing 91.18% of the dysregulated signaling pathways in macrophages and 100% of the dysregulated signaling pathways in lung epithelial cells. Additionally， YQPWP had the function of scattering wind and clearing heat， resolving toxins and removing dampness in accordance with the pathogenesis of wind-heat with dampness in COVID-19. It was selected as the basic formula， and was further modified and optimized to develop an innovative fomula Qiaobang Zhupi Yin （翘蒡术皮饮， QBZPY） based on expert experience and artificial intelligence in composing formulae. QBZPY can reverse all the dysregulated signaling pathways associated with COVID-19 in macrophages and lung epithelial cells， with the reversing rates of 100%. The chief medicinal of QBZPY， including Lianqiao （Fructus Forsythiae）， Xixiancao （Herba Siegesbeckiae） and Niubangzi （Fructus Arctii）， can down-regulate multiple signaling pathways related with virus infection， immune response， and epithelial damage. RT-qPCR results indicated that compared with the model group， the QBZPY group down-regulated the mRNA expression of Il1b， tumor necrosis factor （Tnf）， Cxcl2， Cxcl10， Ccl2， Nos2 and Ptgs2 induced by LPS in RAW264.7 cells （P＜0.05 or P＜0.01）. ConclusionBased on targeted transcriptome analysis， expert experience in TCM and artificial intelligence， QBZPY has been developed for the treatment of nonsevere COVID-19. The ethanol extract of QBZPY has been found to inhibit mRNA expression of several pro-inflammatory genes in a cellular inflammation model.

Objective To observe the efficacy and safety of Morinda officinalis oligosaccharides in the continuation treatment of mild and moderate depression.Methods An open,single-arm,multi-center design was adopted in our study.Adult patients with mild and moderate depression who had received acute treatment of Morinda officinalis oligosaccharides were enrolled and continue to receive Morinda officinalis oligosaccharides capsules for 24 weeks,the dose remained unchanged during continuation treatment.The remission rate,recurrence rate,recurrence time,and the change from baseline to endpoint of Hamilton Depression Scale(HAMD),Hamilton Anxiety Scale(HAMA),Clinical Global Impression-Severity(CGI-S)and Arizona Sexual Experience Scale(ASEX)were evaluated.The incidence of treatment-related adverse events was reported.Results The scores of HAMD-17 at baseline and after treatment were 6.60±1.87 and 5.85±4.18,scores of HAMA were 6.36±3.02 and 4.93±3.09,scores of CGI-S were 1.49±0.56 and 1.29±0.81,scores of ASEX were 15.92±4.72 and 15.57±5.26,with significant difference(P＜0.05).After continuation treatment,the remission rate was 54.59％(202 cases/370 cases),and the recurrence rate was 6.49％(24 cases/370 cases),the recurrence time was(64.67±42.47)days.The incidence of treatment-related adverse events was 15.35％(64 cases/417 cases).Conclusion Morinda officinalis oligosaccharides capsules can be effectively used for the continuation treatment of mild and moderate depression,and are well tolerated and safe.

Objective:To investigate the feasibility and accuracy of computer vision-based artificial intelligence technology in detecting and recognizing instruments and organs in the scenario of radical laparoscopic gastrectomy for gastric cancer.Methods:Eight complete laparoscopic distal radical gastrectomy surgery videos were collected from four large tertiary hospitals in China (First Medical Center of Chinese PLA General Hospital [three cases], Liaoning Cancer Hospital [two cases], Liyang Branch of Jiangsu Province People's Hospital [two cases], and Fudan University Shanghai Cancer Center [one case]). PR software was used to extract frames every 5–10 seconds and convert them into image frames. To ensure quality, deduplication was performed manually to remove obvious duplication and blurred image frames. After conversion and deduplication, there were 3369 frame images with a resolution of 1,920×1,080 PPI. LabelMe was used for instance segmentation of the images into the following 23 categories: veins, arteries, sutures, needle holders, ultrasonic knives, suction devices, bleeding, colon, forceps, gallbladder, small gauze, Hem-o-lok, Hem-o-lok appliers, electrocautery hooks, small intestine, hepatogastric ligaments, liver, omentum, pancreas, spleen, surgical staplers, stomach, and trocars. The frame images were randomly allocated to training and validation sets in a 9:1 ratio. The YOLOv8 deep learning framework was used for model training and validation. Precision, recall, average precision (AP), and mean average precision (mAP) were used to evaluate detection and recognition accuracy.Results:The training set contained 3032 frame images comprising 30 895 instance segmentation counts across 23 categories. The validation set contained 337 frame images comprising 3407 instance segmentation counts. The YOLOv8m model was used for training. The loss curve of the training set showed a smooth gradual decrease in loss value as the number of iteration calculations increased. In the training set, the AP values of all 23 categories were above 0.90, with a mAP of 0.99, whereas in the validation set, the mAP of the 23 categories was 0.82. As to individual categories, the AP values for ultrasonic knives, needle holders, forceps, gallbladders, small pieces of gauze, and surgical staplers were 0.96, 0.94, 0.91, 0.91, 0.91, and 0.91, respectively. The model successfully inferred and applied to a 5-minutes video segment of laparoscopic gastroenterostomy suturing.Conclusion:The primary finding of this multicenter study is that computer vision can efficiently, accurately, and in real-time detect organs and instruments in various scenarios of radical laparoscopic gastrectomy for gastric cancer.

Endodontic diseases are a kind of chronic infectious oral disease.Common endodontic treatment concepts are based on the removal of inflamed or necrotic pulp tissue and the replacement by gutta-percha.However,it is very essential for endodontic treatment to debride the root canal system and prevent the root canal system from bacterial reinfection after root canal therapy(RCT).Recent research,encompassing bacterial etiology and advanced imaging techniques,contributes to our understanding of the root canal system's anatomy intricacies and the technique sensitivity of RCT.Success in RCT hinges on factors like patients,infection severity,root canal anatomy,and treatment techniques.Therefore,improving disease management is a key issue to combat endodontic diseases and cure periapical lesions.The clinical difficulty assessment system of RCT is established based on patient conditions,tooth conditions,root canal configuration,and root canal needing retreatment,and emphasizes pre-treatment risk assessment for optimal outcomes.The findings suggest that the presence of risk factors may correlate with the challenge of achieving the high standard required for RCT.These insights contribute not only to improve education but also aid practitioners in treatment planning and referral decision-making within the field of endodontics.

Objective To investigate the incidence rate,clinical characteristics,and prognosis of neonatal stroke in Shenzhen,China.Methods Led by Shenzhen Children's Hospital,the Shenzhen Neonatal Data Collaboration Network organized 21 institutions to collect 36 cases of neonatal stroke from January 2020 to December 2022.The incidence,clinical characteristics,treatment,and prognosis of neonatal stroke in Shenzhen were analyzed.Results The incidence rate of neonatal stroke in 21 hospitals from 2020 to 2022 was 1/15 137,1/6 060,and 1/7 704,respectively.Ischemic stroke accounted for 75％(27/36);boys accounted for 64％(23/36).Among the 36 neonates,31(86％)had disease onset within 3 days after birth,and 19(53％)had convulsion as the initial presentation.Cerebral MRI showed that 22 neonates(61％)had left cerebral infarction and 13(36％)had basal ganglia infarction.Magnetic resonance angiography was performed for 12 neonates,among whom 9(75％)had involvement of the middle cerebral artery.Electroencephalography was performed for 29 neonates,with sharp waves in 21 neonates(72％)and seizures in 10 neonates(34％).Symptomatic/supportive treatment varied across different hospitals.Neonatal Behavioral Neurological Assessment was performed for 12 neonates(33％,12/36),with a mean score of(32±4)points.The prognosis of 27 neonates was followed up to around 12 months of age,with 44％(12/27)of the neonates having a good prognosis.Conclusions Ischemic stroke is the main type of neonatal stroke,often with convulsions as the initial presentation,involvement of the middle cerebral artery,sharp waves on electroencephalography,and a relatively low neurodevelopment score.Symptomatic/supportive treatment is the main treatment method,and some neonates tend to have a poor prognosis.

Patient 1,a 12-day-old female infant,presented with fever,cough,dyspnea,and elevated infection markers,requiring respiratory support.Metagenomic next-generation sequencing(mNGS)of blood and bronchoalveolar lavage fluid revealed Legionella pneumophila(LP),leading to diagnoses of LP pneumonia and LP sepsis.The patient was treated with erythromycin for 15 days and azithromycin for 5 days,resulting in recovery and discharge.Patient 2,an 11-day-old female infant,presented with dyspnea,fever,elevated infection markers,and multiple organ dysfunction,requiring mechanical ventilation.mNGS of blood and cerebrospinal fluid indicated LP,leading to diagnoses of LP pneumonia,LP sepsis,and LP intracranial infection.The patient was treated with erythromycin for 19 days and was discharged after recovery.Neonatal LP pneumonia lacks specific clinical symptoms,and azithromycin is the preferred antimicrobial agent.The use of mNGS can provide early and definitive diagnosis for severe neonatal pneumonia of unknown origin.

Objective:To investigate the feasibility and accuracy of computer vision-based artificial intelligence technology in detecting and recognizing instruments and organs in the scenario of radical laparoscopic gastrectomy for gastric cancer.Methods:Eight complete laparoscopic distal radical gastrectomy surgery videos were collected from four large tertiary hospitals in China (First Medical Center of Chinese PLA General Hospital [three cases], Liaoning Cancer Hospital [two cases], Liyang Branch of Jiangsu Province People's Hospital [two cases], and Fudan University Shanghai Cancer Center [one case]). PR software was used to extract frames every 5–10 seconds and convert them into image frames. To ensure quality, deduplication was performed manually to remove obvious duplication and blurred image frames. After conversion and deduplication, there were 3369 frame images with a resolution of 1,920×1,080 PPI. LabelMe was used for instance segmentation of the images into the following 23 categories: veins, arteries, sutures, needle holders, ultrasonic knives, suction devices, bleeding, colon, forceps, gallbladder, small gauze, Hem-o-lok, Hem-o-lok appliers, electrocautery hooks, small intestine, hepatogastric ligaments, liver, omentum, pancreas, spleen, surgical staplers, stomach, and trocars. The frame images were randomly allocated to training and validation sets in a 9:1 ratio. The YOLOv8 deep learning framework was used for model training and validation. Precision, recall, average precision (AP), and mean average precision (mAP) were used to evaluate detection and recognition accuracy.Results:The training set contained 3032 frame images comprising 30 895 instance segmentation counts across 23 categories. The validation set contained 337 frame images comprising 3407 instance segmentation counts. The YOLOv8m model was used for training. The loss curve of the training set showed a smooth gradual decrease in loss value as the number of iteration calculations increased. In the training set, the AP values of all 23 categories were above 0.90, with a mAP of 0.99, whereas in the validation set, the mAP of the 23 categories was 0.82. As to individual categories, the AP values for ultrasonic knives, needle holders, forceps, gallbladders, small pieces of gauze, and surgical staplers were 0.96, 0.94, 0.91, 0.91, 0.91, and 0.91, respectively. The model successfully inferred and applied to a 5-minutes video segment of laparoscopic gastroenterostomy suturing.Conclusion:The primary finding of this multicenter study is that computer vision can efficiently, accurately, and in real-time detect organs and instruments in various scenarios of radical laparoscopic gastrectomy for gastric cancer.