Neddylation is a crucial posttranslational modification that involves the attachment of neural precursor cell-expressed developmentally downregulated protein 8 (NEDD8) to a lysine residue in the substrate via the sequential actions of the E1 NEDD8-activating enzyme (NAE) (E1), E2 NEDD8-conjugating enzyme (E2), and E3 NEDD8-ligase (E3). The most extensively studied substrates of neddylation are members of the cullin family, which act as scaffold components for cullin ring E3 ubiquitin ligases (CRLs). Since cullin neddylation activates CRLs, which are frequently overactive in tumors, inhibiting neddylation has emerged as a promising strategy for developing novel antitumor therapies. This review explores the antitumor effects of inhibiting neddylation that leads to the inactivation of CRLs and provides a summary of known inhibitors that target protein-protein interactions (PPIs) within the neddylation enzymatic cascade.

Neddylation is a crucial posttranslational modification that involves the attachment of neural precursor cell-expressed developmentally downregulated protein 8(NEDD8)to a lysine residue in the substrate via the sequential actions of the E1 NEDD8-activating enzyme(NAE)(E1),E2 NEDD8-conjugating enzyme(E2),and E3 NEDD8-ligase(E3).The most extensively studied substrates of neddylation are members of the cullin family,which act as scaffold components for cullin ring E3 ubiquitin ligases(CRLs).Since cullin neddylation activates CRLs,which are frequently overactive in tumors,inhibiting neddylation has emerged as a promising strategy for developing novel antitumor therapies.This review explores the antitumor effects of inhibiting neddylation that leads to the inactivation of CRLs and provides a summary of known inhibitors that target protein-protein interactions(PPIs)within the neddylation enzymatic cascade.

Objective:To explore the independent factors influencing extraprostatic extension (EPE) after radical prostatectomy(RP) in patients with clinically localized prostate cancer by utilizing the Surveillance, Epidemiology, and End Results (SEER) database. A nomogram model was developed and externally validated.Methods:Clinical and pathological data of 20 916 clinically localized prostate cancer patients (T 1-2N 0M 0) who underwent RP between 2010 and 2021 were extracted from the SEER database. The mean age was (61.71±7.09) years old, and a total of 17 835 patients (85.3%) were married.There were 2 243 patients (10.7%) with prostate-specific antigen (PSA) <4 ng/ml, 14 831 patients (70.9%) with ≥4 and <10 ng/ml, and 2 965 patients (14.2%) with ≥10 and <20 ng/ml. There were 14 870 patients (71.1%) with clinical staging of stage T 1, and 6 046 patients (28.9%) with T 2. There were 48 patients (0.2%) with pathological staging of stage T 1, 15 794 (75.5%) with T 2, 5 001(23.9%) with T 3, and 73 (0.3%) with T 4 stage after radical surgery.The patients of SEER database were divided into training and internal validation groups in a 7∶3 ratio by using stratified sampling. Additionally, data were collected for 75 clinically localized prostate cancer patients who underwent RP at the Second Affiliated Hospital of Zhengzhou University from September 2019 to September 2024, serving as the external validation group.The mean age was(65.39±7.45) years old. Among them, 73 (97.3%) were married. There were 2 patients (2.7%) with PSA <4 ng/ml, 17 patients (22.7%) with ≥4 and <10 ng/ml, and 34 patients (45.3%) with ≥10 and <20 ng/ml. There were 47 patients (62.7%) with clinical staging of stage T 1, and 28 patients (37.3%) with T 2. There were 7 patients (9.3%) with pathological staging of stage T 1, 48 patients (64.0%)with T 2, 18 patients (24.0%) with T 3, and 2 patients (2.7%) with T 4 stage after radical surgery. All patients were categorized into organ-confined (OC) and EPE groups based on post-surgical pathology. Univariate and multivariate logistic regression analyses, with a stepwise backward selection, were performed on the training group to identify independent risk factors of EPE, which were used to construct a nomogram model. Model performance was assessed using receiver operating characteristic (ROC) curve area under the curve (AUC), calibration curves, and decision curve analysis (DCA) for the training group, internal validation group, and external validation group. Results:EPE was observed in 3 585 cases (24.5%), 1 489 cases (23.8%), and 20 cases (26.7%) in the training, internal validation, and external validation groups, respectively. Logistic regression analyses identified preoperative age ( OR=1.026, P<0.001), PSA levels (≥10 and <20 ng/ml: OR=1.790, P<0.001; ≥20 ng/ml: OR=2.683, P<0.001), tumor maximum diameter (10-20 mm: OR=2.051, P<0.001; >20 mm: OR=3.937, P<0.001), biopsy Gleason score (score 7: OR=1.911, P<0.001; score 8: OR=2.906, P<0.001; score 9: OR = 5.278, P<0.001; score 10: OR=4.421, P=0.003), number of positive biopsy cores (≥4 cores: OR=1.260, P<0.001), and their proportion of total cores ( OR=1.012, P<0.001) as independent predictors of EPE. The nomogram model demonstrated good predictive performance, with AUC of 0.741, 0.748, and 0.724 in the training, internal validation, and external validation groups, respectively. Calibration and DCA curves confirmed the model’s excellent stability and generalizability. Conclusions:Age, PSA levels, maximum tumor diameter, biopsy Gleason score, number of positive biopsy cores, and their proportion of total cores are independent predictors of EPE after RP in clinically localized prostate cancer. The constructed model effectively predicts the risk of EPE occurrence.

Objective:To explore the independent factors influencing extraprostatic extension (EPE) after radical prostatectomy(RP) in patients with clinically localized prostate cancer by utilizing the Surveillance, Epidemiology, and End Results (SEER) database. A nomogram model was developed and externally validated.Methods:Clinical and pathological data of 20 916 clinically localized prostate cancer patients (T 1-2N 0M 0) who underwent RP between 2010 and 2021 were extracted from the SEER database. The mean age was (61.71±7.09) years old, and a total of 17 835 patients (85.3%) were married.There were 2 243 patients (10.7%) with prostate-specific antigen (PSA) <4 ng/ml, 14 831 patients (70.9%) with ≥4 and <10 ng/ml, and 2 965 patients (14.2%) with ≥10 and <20 ng/ml. There were 14 870 patients (71.1%) with clinical staging of stage T 1, and 6 046 patients (28.9%) with T 2. There were 48 patients (0.2%) with pathological staging of stage T 1, 15 794 (75.5%) with T 2, 5 001(23.9%) with T 3, and 73 (0.3%) with T 4 stage after radical surgery.The patients of SEER database were divided into training and internal validation groups in a 7∶3 ratio by using stratified sampling. Additionally, data were collected for 75 clinically localized prostate cancer patients who underwent RP at the Second Affiliated Hospital of Zhengzhou University from September 2019 to September 2024, serving as the external validation group.The mean age was(65.39±7.45) years old. Among them, 73 (97.3%) were married. There were 2 patients (2.7%) with PSA <4 ng/ml, 17 patients (22.7%) with ≥4 and <10 ng/ml, and 34 patients (45.3%) with ≥10 and <20 ng/ml. There were 47 patients (62.7%) with clinical staging of stage T 1, and 28 patients (37.3%) with T 2. There were 7 patients (9.3%) with pathological staging of stage T 1, 48 patients (64.0%)with T 2, 18 patients (24.0%) with T 3, and 2 patients (2.7%) with T 4 stage after radical surgery. All patients were categorized into organ-confined (OC) and EPE groups based on post-surgical pathology. Univariate and multivariate logistic regression analyses, with a stepwise backward selection, were performed on the training group to identify independent risk factors of EPE, which were used to construct a nomogram model. Model performance was assessed using receiver operating characteristic (ROC) curve area under the curve (AUC), calibration curves, and decision curve analysis (DCA) for the training group, internal validation group, and external validation group. Results:EPE was observed in 3 585 cases (24.5%), 1 489 cases (23.8%), and 20 cases (26.7%) in the training, internal validation, and external validation groups, respectively. Logistic regression analyses identified preoperative age ( OR=1.026, P<0.001), PSA levels (≥10 and <20 ng/ml: OR=1.790, P<0.001; ≥20 ng/ml: OR=2.683, P<0.001), tumor maximum diameter (10-20 mm: OR=2.051, P<0.001; >20 mm: OR=3.937, P<0.001), biopsy Gleason score (score 7: OR=1.911, P<0.001; score 8: OR=2.906, P<0.001; score 9: OR = 5.278, P<0.001; score 10: OR=4.421, P=0.003), number of positive biopsy cores (≥4 cores: OR=1.260, P<0.001), and their proportion of total cores ( OR=1.012, P<0.001) as independent predictors of EPE. The nomogram model demonstrated good predictive performance, with AUC of 0.741, 0.748, and 0.724 in the training, internal validation, and external validation groups, respectively. Calibration and DCA curves confirmed the model’s excellent stability and generalizability. Conclusions:Age, PSA levels, maximum tumor diameter, biopsy Gleason score, number of positive biopsy cores, and their proportion of total cores are independent predictors of EPE after RP in clinically localized prostate cancer. The constructed model effectively predicts the risk of EPE occurrence.

Objective:To investigate the application value of combining Prostate Imaging Reporting and Data System (PI-RADS v2.1) score and Systemic Immune-Inflammation Index (SII) in predicting pathological upgrading in patients with localized prostate cancer after radical prostatectomy(RP).Methods:A retrospective analysis was conducted on clinical data from 76 patients with localized prostate cancer who underwent prostate biopsy and radical prostatectomy at the Second Affiliated Hospital of Zhengzhou University between September 2019 and May 2024. The median age was 68 (65, 71) years. Total prostate-specific antigen (tPSA) was 17.4 (8.4, 30.9) ng/ml, and prostate volume was 43.1 (29.9, 58.9) ml. PI-RADS scores were ≤3 in 22 cases (28.9%) and >3 in 54 cases (71.1%). According to the International Society of Urological Pathology (ISUP) grading of biopsy specimens, 31 patients (40.8%) were classified as Group <3 and 45 patients (59.2%) as Group ≥3. Postoperatively, 25 patients (32.9%) were classified as ISUP Group <3, and 51 patients (67.1%) as Group ≥3. Pathological upgrading was defined as either: ①a higher ISUP grade in postoperative specimens compared to biopsy specimens or; ②benign prostate tissue identified in biopsy specimens but confirmed as prostate cancer postoperatively. Clinical data were compared between the pathological upgrade and non-upgrade groups. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for pathological upgrading and to construct a nomogram model. Receiver operating characteristic (ROC) curves were used to evaluate the predictive performance of individual indicators (PI-RADS, SII, %PSA, and the proportion of tumor tissue in biopsy specimens) and the combined nomogram model. Internal validation was conducted using cross-validation, and calibration and decision curves were generated to assess the nomogram′s accuracy and clinical net benefit.Results:Among the 76 patients included, 10 (13.2%) experienced pathological downgrading, 36 (47.4%) had consistent grading, and 30 (39.5%) experienced pathological upgrading. The platelet-to-lymphocyte ratio (PLR) [118.2(93.5, 139.1) vs. 95.2(79.3, 116.4), P=0.021], SII [394.8(331.0, 513.6) vs. 338.8(217.2, 407.8), P=0.002], and the number of cases with a PI-RADS score >3 [26 cases(86.7%) vs. 28 cases(60.9%), P=0.015] were significantly higher in the pathological upgrade group than in the non-upgrade group. Conversely, the percentage of positive biopsy cores [35.9%(12.6%, 51.8%) vs. 43.8%(21.0%, 92.1%), P=0.045], the proportion of tumor tissue in biopsy specimens [6.9%(1.3%, 20.1%) vs. 19.3%(9.1%, 58.4%), P<0.01], and the number of cases in ISUP biopsy Group ≥3 [12 cases (40.0%) vs. 33 cases (71.7%), P=0.006] were significantly lower in the upgrade group (all P < 0.05). Univariate and multivariate logistic regression analyses showed that PI-RADS score( OR=17.111, 95% CI 2.388-122.592, P<0.01), SII( OR=1.009, 95% CI 1.001-1.016, P=0.028), %PSA ( OR=0.003, 95% CI 0.002-0.004, P<0.01), and the proportion of tumor tissue in biopsy specimens ( OR=0.899, 95% CI 0.837-0.966, P<0.01) were independent predictors of pathological upgrading. The area under the ROC curve (AUC) for PI-RADS, SII, %PSA, and the proportion of tumor tissue in biopsy specimens were 0.607, 0.711, 0.618, and 0.778, respectively. The combined AUC for %PSA and the proportion of tumor tissue was 0.791, while the combined AUC of the four-indicator nomogram model was 0.914. The DeLong test indicated a statistically significant difference in diagnostic performance between the two models ( P<0.01). Calibration and decision curves demonstrated good accuracy and clinical net benefit for the nomogram model. Conclusions:The PI-RADS v2.1 score and SII have significant predictive value for pathological upgrading after radical prostatectomy in prostate cancer. A nomogram model combining PI-RADS, SII, %PSA, and the proportion of tumor tissue in biopsy specimens shows excellent predictive performance.

Objective:To investigate the application value of combining Prostate Imaging Reporting and Data System (PI-RADS v2.1) score and Systemic Immune-Inflammation Index (SII) in predicting pathological upgrading in patients with localized prostate cancer after radical prostatectomy(RP).Methods:A retrospective analysis was conducted on clinical data from 76 patients with localized prostate cancer who underwent prostate biopsy and radical prostatectomy at the Second Affiliated Hospital of Zhengzhou University between September 2019 and May 2024. The median age was 68 (65, 71) years. Total prostate-specific antigen (tPSA) was 17.4 (8.4, 30.9) ng/ml, and prostate volume was 43.1 (29.9, 58.9) ml. PI-RADS scores were ≤3 in 22 cases (28.9%) and >3 in 54 cases (71.1%). According to the International Society of Urological Pathology (ISUP) grading of biopsy specimens, 31 patients (40.8%) were classified as Group <3 and 45 patients (59.2%) as Group ≥3. Postoperatively, 25 patients (32.9%) were classified as ISUP Group <3, and 51 patients (67.1%) as Group ≥3. Pathological upgrading was defined as either: ①a higher ISUP grade in postoperative specimens compared to biopsy specimens or; ②benign prostate tissue identified in biopsy specimens but confirmed as prostate cancer postoperatively. Clinical data were compared between the pathological upgrade and non-upgrade groups. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for pathological upgrading and to construct a nomogram model. Receiver operating characteristic (ROC) curves were used to evaluate the predictive performance of individual indicators (PI-RADS, SII, %PSA, and the proportion of tumor tissue in biopsy specimens) and the combined nomogram model. Internal validation was conducted using cross-validation, and calibration and decision curves were generated to assess the nomogram′s accuracy and clinical net benefit.Results:Among the 76 patients included, 10 (13.2%) experienced pathological downgrading, 36 (47.4%) had consistent grading, and 30 (39.5%) experienced pathological upgrading. The platelet-to-lymphocyte ratio (PLR) [118.2(93.5, 139.1) vs. 95.2(79.3, 116.4), P=0.021], SII [394.8(331.0, 513.6) vs. 338.8(217.2, 407.8), P=0.002], and the number of cases with a PI-RADS score >3 [26 cases(86.7%) vs. 28 cases(60.9%), P=0.015] were significantly higher in the pathological upgrade group than in the non-upgrade group. Conversely, the percentage of positive biopsy cores [35.9%(12.6%, 51.8%) vs. 43.8%(21.0%, 92.1%), P=0.045], the proportion of tumor tissue in biopsy specimens [6.9%(1.3%, 20.1%) vs. 19.3%(9.1%, 58.4%), P<0.01], and the number of cases in ISUP biopsy Group ≥3 [12 cases (40.0%) vs. 33 cases (71.7%), P=0.006] were significantly lower in the upgrade group (all P < 0.05). Univariate and multivariate logistic regression analyses showed that PI-RADS score( OR=17.111, 95% CI 2.388-122.592, P<0.01), SII( OR=1.009, 95% CI 1.001-1.016, P=0.028), %PSA ( OR=0.003, 95% CI 0.002-0.004, P<0.01), and the proportion of tumor tissue in biopsy specimens ( OR=0.899, 95% CI 0.837-0.966, P<0.01) were independent predictors of pathological upgrading. The area under the ROC curve (AUC) for PI-RADS, SII, %PSA, and the proportion of tumor tissue in biopsy specimens were 0.607, 0.711, 0.618, and 0.778, respectively. The combined AUC for %PSA and the proportion of tumor tissue was 0.791, while the combined AUC of the four-indicator nomogram model was 0.914. The DeLong test indicated a statistically significant difference in diagnostic performance between the two models ( P<0.01). Calibration and decision curves demonstrated good accuracy and clinical net benefit for the nomogram model. Conclusions:The PI-RADS v2.1 score and SII have significant predictive value for pathological upgrading after radical prostatectomy in prostate cancer. A nomogram model combining PI-RADS, SII, %PSA, and the proportion of tumor tissue in biopsy specimens shows excellent predictive performance.

Objective:To investigate the safety and feasibility of the CHESS endoscpic ruler (CHESS ruler), and the consistency between the measured values and the interpretation values by endoscopic physician experience.Methods:From January 2021 to January 2022, a total of 105 liver cirrhosis patients with portal hypertension were prospectively enrolled from General Hospital, Xixia Branch Hospital, Ningnan Hospital of People′s Hospital of Ningxia Hui Autonomous Region (29 cases), and the First People′s Hospital of Yinchuan (25 cases), General Hospital of Ningxia Medical University (18 cases), Wuzhong People′s Hospital (10 cases), the Fifth People′s Hospital of Ningxia Hui Autonomous Region (10 cases), Shizuishan Second People′s Hospital (6 cases), Yinchuan Second People′s Hospital (5 cases), and Zhongwei People′s Hospital (2 cases) 8 hospitals. The clinical characteristics of all the patients, including gender, age, nationality, etiolog of liver cirrhosis, and Child-Pugh classification of liver function were recorded. A big gastroesophageal varices was defined as diameter of varices ≥5 mm. Endoscopist (associated chief physician) performed gastroscopy according to the routine gastroscopy procedures, and the diameter of the biggest esophageal varices was measured by experience and images were collected, and then objective measurement was with the CHESS ruler and images were collected. The diameter of esophageal varices of 10 randomly selected patients (random number table method) was determined by 6 endoscopists (attending physician or associated chief physician) with experience or measured by CHESS ruler. Kappa test was used to test the consistency in the diameter of esophageal varices between measured values by CHESS ruler and the interpretation values by endoscopic physician experience.Results:Among 105 liver cirrhosis patients with portal hypertension, male 65 cases and female 40 cases, aged (54.8±12.2) years old, Han nationality 82 cases, Hui nationality 21 cases and Mongolian nationality 2 cases. The etiology of liver cirrhosis included chronic hepatitis B (79 cases), alcoholic liver disease (7 cases), autoimmune hepatitis (7 cases), chronic hepatitis C (2 cases), and other etiology (10 cases). Liver function of 32 cases was Child-Pugh A, Child-Pugh B 57 cases, and Child-Pugh C 16 cases. All 105 liver cirrhosis patients with cirrhotic portal hypertension were successfully measured the diameter of gastroesophageal varices by CHESS ruler, and the success rate of application of CHESS ruler was 100.0% (105/105). The procedure time from the CHESS ruler into the body to the exit of the body after measurement was (3.50±2.55) min. No complications happened in all the patients during measurement. Among 105 liver cirrhosis patients with cirrhotic portal hypertension, 96 cases (91.4%) were recognized as big gastroesophageal varices by the endoscopists. Totally 93 cases (88.6%) were considered as big gastroesophageal varices by CHESS ruler. Eight cases were recognized as big gastroesophageal varices by the endoscopist, however not by the CHESS ruler; 5 cases were recognized as big gastroesophageal varices by the CHESS ruler, but not by the endoscopists; 4 cases were not recognized as big gastroesophageal varices both by the endoscopists and CHESS ruler; 88 cases were recognized as big gastroesophageal varices both by the endoscopists and CHESS ruler. The missed diagnostic rate of big gastroesophageal varices by the endoscopists experience was 5.4% (5/93), and the Kappa value of consistency coefficient between the measurement by the CHESS ruler and the interpretation by endoscopists experience was 0.31 (95% confidence interval 0.03 to 0.60). The overall Kappa value of consistency coefficient by 6 endoscopists measured by CHESS ruler in big gastroesophageal varices diagnosis was 0.77 (95% confidence interval 0.61 to 0.93).Conclusion:As an objective measurement tool, CHESS ruler can make up for the deficiency of subjective judgment by endoscopists, accurately measure the diameter of gastroesophageal varices, and is highly feasible and safe.

Neonatal hyperbilirubinaemia, clinically presenting as jaundice, is a ubiquitous and commonly a benign metabolic condition in newborn infants.It is a leading cause of hospitalization of neonates in the first week of life.Serum bilirubin has been considered as the most potent superoxide with the peroxyl radical scavenger activity.However, uncontrolled hyperbilirubinaemia or rapidly rising bilirubin can reach a neurotoxic concentration, potentially leading to central nervous system sequelae.Thus, the health status of jaundiced newborn infants is dependent on striking an appropriate balance between the protective effects of serum bilirubin and the risk of bilirubin neurotoxicity.In order to standardize the management of neonatal hyperbilirubinemia (jaundice), many countries have developed clinical practice management guidelines.This review sorted out and briefly interpreted the main contents of clinical management guidelines for neonatal hyperbilirubinemia drafted by the American Academy of Pediatrics and other countries, aiming to provide references of clinical diagnosis and treatment practice to domestic pediatrician.

Objective:To investigate the effect of lappaconitine (LA) on neuropathic pain (NPP) mediated by retrograde transport of purinergic P2X3 receptor (P2X3R) in dorsal root ganglion (DRG) neurons of rats with chronic constriction injury (CCI) of the sciatic nerve.Methods:Seventy-two male healthy SD rats were selected to construct the NPP model following CCI of the sciatic nerve by ligating the right sciatic nerve. according to the random number table method. The rats were divided into CCI group, CCI+LA group and normal control group according to the random number table method, with 24 rats in each group. In normal control group, the right sciatic nerve was exposed without ligation. In CCI+LA group, the rats were given 2 g/L LA (ie, 4 mg/kg intravenously for once a day for one day only) after the same treatment as CCI group. Other two groups were injected with the identical amount of normal saline in the same way. The mechanical paw withdrawal threshold (MWT) and thermal paw withdrawal latency (TWL) were evaluated before injury and at 2, 6, 12 and 24 hours after injury to evaluate the symptoms of neuralgia caused by nerve injury. The proximal and distal nerve fragments were collected in the three groups at 2, 6, 12 and 24 hours after injury. Western blotting was applied to analyze the expression of P2X3R at 2, 6, 12 and 24 hours after injury and the expression of neurotrophic factor (NGF) and tyrosine kinase receptor A (TrkA) at 24 hours after injury to evaluate the effect of LA on P2X3R, NGF and TrkA.Results:There were insignificant differences in MWT and TWL among all groups before injury (all P>0.05). Compared with normal control group, MWT and TWL were significantly decreased in CCI group and CCI+LA group at 2, 6, 12 and 24 hours after injury (all P<0.05 or 0.01). There were insignificant differences in MWT and TWL between CCI group and CCI+LA group at 2 and 6 hours after injury (all P>0.05), while MWT and TWL were significantly higher in CCI+LA group than those in CCI group at 12 and 24 hours after injury (all P<0.05 or 0.01). In the proximal sciatic nerve segment, Western blotting showed similar levels of P2X3R among all groups at 2, 6, 12 and 24 hours after injury (all P>0.05). In the distal sciatic nerve segment, Western blotting showed higher expression of P2X3R in CCI group than that in normal control group at 2, 6, 12, 24 hours after injury (all P<0.01), higher expression of P2X3R in CCI+LA group than that in normal control group at 2, 6 and 12 hours after injury (all P<0.05), similar expression of P2X3R expression between CCI+LA group and normal control group at 24 hours after injury ( P>0.05), similar expression of P2X3R between CCI group and CCI+LA group at 2 and 6 hours after injury (all P>0.05), and lower expression of P2X3R in CCI+LA group than that in CCI group at 12 and 24 hours after injury ( P<0.05 or 0.01). In the proximal and distal nerve fragments, the expression of NGF was lower in normal control group than that in CCI group and CCI+LA group ( P<0.05 or 0.01), but was similar between CCI group and CCI+LA group at 24 hours after injury ( P>0.05). In the proximal and distal nerve fragments, there were insignificant differences in the expression of TrkA among all groups at 24 hours after injury (all P>0.05). Conclusion:Early LA treatment after injury can alleviate mechanical and thermal hyperalgesia in NPP rats, which may be related to the reduction of P2X3R retrograde transport in DRG neuron axonal.

An epidemiological investigation was carried out on a local cluster of outbreak caused by imported cases of Coronavirus Disease 2019 (COVID-19) in rural areas of Chengdu in December 2020, to find out the source of infection and the chain of transmission. According to
COVID-19 ; Disease Outbreaks ; Epidemics ; Humans ; Quarantine ; SARS-CoV-2