ObjectiveEarly blight is a common destructive disease in the growth process of Solanaceae crops, which can lead to crop failure and serious losses. Traditional crop disease detection methods are difficult to detect disease characteristics in a timely manner during the incubation period of disease, and thus take scientific and effective prevention and control measures. This study obtained hyperspectral images of early blight of peppers at different infection stages through continuous monitoring with a hyperspectral imager. The earliest identifiable time during the incubation period of early blight in peppers (the earliest identifiable time during the incubation period in this experiment was 24 h after inoculation) was determined using the spectral angle cosine-correlation coefficient and Chebyshev distance. MethodsTaking the symptoms of the latent period of early blight in peppers as the research object, 13 characteristic wavelengths were selected using a genetic algorithm. An identification model of crop disease latent period symptoms based on spectral features was established through optimized combinations of characteristic wavelengths combined with a logistic regression model. Simultaneously, a recognition model of the latent period of early blight in peppers based on image texture features was established using local binary patterns. ResultsThe experiment was tested with 120 samples. The accuracy of the identification model of crop disease latent period symptoms based on spectral features reached over 93% in both the training set and the test set. The accuracy of the identification model of crop disease latent period symptoms based on texture features reached 98.96% and 100% in the training set and test set, respectively. ConclusionBoth spectral features and texture features can be used to detect and identify crop disease latent period symptoms. Texture features more significantly revealed the characteristics of the latent period of the disease compared to spectral features, effectively improving the detection performance of the model. The research results in this article can provide theoretical references for monitoring and identifying other crop disease latent period symptoms.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

BACKGROUND:Combined radiation and wound injury appeared mainly in patients with tumor radiotherapy and nuclear radiation accidents.The radiation destroys the repair mechanism,resulting in delayed or prolonged wound healing.It still lacks an effective therapeutic strategy currently. OBJECTIVE:To prepare multifunctional wound dressings based on the multiple clinical symptoms of combined radiation and wound injury,which are designed to be antibacteria,promoted healing and analgesics. METHODS:Using levofloxacin,fibroin and lidocaine hydrochloride as raw materials,3D bioprinting technology was applied to prepare the multifunctional wound dressing.(1)The multifunctional dressing was placed on a fixed culture plate coated with Staphylococcus aureus,Escherichia coli and Pseudomonas aeruginosa,and incubated at 37 ℃ overnight to detect the diameter of the antibacterial zone.(2)40 Kunming mice were randomly divided into trauma group,radiation and trauma model group,treatment group and positive drug group,with 10 mice in each group.Mice in the radiation and trauma model group,treatment group and positive drug group were irradiated by 60Co gamma rays.After 1 hour of radiation,a full-layer skin defect wound with a diameter of 1 cm was made on the back of each mouse in the four groups.Normal saline was applied to the wounds of the trauma group and the radiation and trauma model group.Trethanolamine cream was applied to the wounds of the positive drug group.Multifunctional dressing was applied to the wounds of the treatment group.The dressing was changed every 2 days,and the treatment was continued for 14 days.Wound healing rate and serum interleukin-6 level were measured at 3,7 and 14 days after wound modeling.14 days after the wound modeling,the skin tissue of the wound was obtained and received hematoxylin-eosin staining,Masson staining and cytokeratin-14 immunohistochemical staining. RESULTS AND CONCLUSION:(1)3D-printed multifunctional wound dressing had good antibacterial activity.The antibacterial zone diameters against Staphylococcus aureus,Escherichia coli and Pseudomonas aeruginosa were(4.15±0.09),(4.18±0.23)and(4.35±0.13)cm,respectively.(2)With the extension of modeling time,the wound healed gradually.The wound healing rate of the treatment group and the positive drug group was higher than that of the radiation and trauma model group at 3,7 and 14 days after modeling(P<0.01,P<0.001).The wound healing rate of the treatment group was higher than that of the positive drug group.With the extension of modeling time,the serum interleukin level of mice increased first and then decreased.The serum interleukin level in the treatment group at 3,7 and 14 days after modeling was lower than that in the radiation and trauma model group.Hematoxylin-eosin staining and Masson staining exhibited that inflammatory cells infiltrated the granuloma tissue in the trauma group,and the dermal collagen fibers were densely arranged.The normal structure of epidermis and dermis was destroyed and inflammatory cells were infiltrated in the radiation and trauma model group.In the treatment group,normal skin mucosal tissue was observed,the epidermis was arranged closely,and the sweat glands,hair follicles and dermal collagen fibers were arranged regularly.In the positive drug group,the arrangement of epidermal layer was tight,and the arrangement of sweat glands,hair follicles and dermal collagen fibers was regular.Cytokeratin-14 immunohistochemical staining displayed that the epidermal tissue thickness in the treatment group was lower than that in the other three groups(P<0.01,P<0.001).(3)The results confirm that the 3D-printed multifunctional dressing has multiple functions of local anesthesia,anti-infection and promoting healing.

ObjectiveTo understand the use of antibiotics in inpatients and the incidence and trend of hospital infections， to explore the implementation effect of comprehensive management measures， and to provide reference for hospitals to use antibiotics reasonably. MethodsBased on the hospital infection monitoring and management system， a retrospective analysis and comparison were conducted on the use of antibiotics， submission of microbial test samples， and incidence of hospital infections among inpatients in a tertiary hospital from 2012 to 2021. ResultsFrom 2012 to 2021， the use of antibiotics showed a downward trend， from 50.82% in 2012 to 41.29% in 2021. At the same time， the use rate of restricted and special antibiotics had also decreased， and the use rate of restricted and special antibiotics in patients without hospital infection was significantly lower than that in patients with hospital infection， and the microbial testing rate was also on the rise. The annual incidence rate of hospital infection was 0.69%‒1.92%， and the annual case-time prevalence rate was 0.79%‒2.17%. The annual average rate of the above two in 10 years was 1.18% and 1.34%， respectively. The results of the exponential smoothing model also showed that the utilization rate of antibiotics was decreasing and the incidence of nosocomial infection was stable. ConclusionLarge general hospitals took comprehensive management measures to strengthen the management of rational use of antibiotics， which led to a decline in the use rate of antibacterial drugs for inpatients and an increase in the rate of microbial examination. At the same time， the overall incidence of hospital infection was relatively stable， suggesting that the comprehensive management measures of antibacterial drugs in hospitals had achieved certain results. The current measures need to be optimized in the future to continuously improve the management level of rational use of antibacterial drugs.

Temporomandibular joint (TMJ) diseases are common clinical conditions. The number of patients with TMJ diseases is large, and the etiology, epidemiology, disease spectrum, and treatment of the disease remain controversial and unknown. To understand and master the current situation of the occurrence, development and prevention of TMJ diseases, as well as to identify the patterns in etiology, incidence, drug sensitivity, and prognosis is crucial for alleviating patients′suffering.This will facilitate in-depth medical research, effective disease prevention measures, and the formulation of corresponding health policies. Cohort construction and research has an irreplaceable role in precise disease prevention and significant improvement in diagnosis and treatment levels. Large-scale cohort studies are needed to explore the relationship between potential risk factors and outcomes of TMJ diseases, and to observe disease prognoses through long-term follw-ups. The consensus aims to establish a standard conceptual frame work for a cohort study on patients with TMJ disease while providing ideas for cohort data standards to this condition. TMJ disease cohort data consists of both common data standards applicable to all specific disease cohorts as well as disease-specific data standards. Common data were available for each specific disease cohort. By integrating different cohort research resources, standard problems or study variables can be unified. Long-term follow-up can be performed using consistent definitions and criteria across different projects for better core data collection. It is hoped that this consensus will be facilitate the development cohort studies of TMJ diseases.

Objective:To investigate the role and underlying mechanisms of methyltransferase (Mettl) 3 in the process of angiotensin Ⅱ (Ang Ⅱ)-induced pericyte-to-myofibroblast transdifferentiation and renal fibrosis.Methods:C57BL/6J mice were used, in cell experiments, mouse renal pericytes were isolated and cultured using magnetic bead sorting. These pericytes were then induced to transdifferentiate into myofibroblasts with 1×10 6 mmol/L Ang Ⅱ, which was the Ang Ⅱ group, while pericytes cultured in normal conditions served as the control group. Successful transdifferentiation was verified by immunofluorescence staining, Western blotting, and real-time reverse transcription PCR (RT-qPCR) for α-smooth muscle actin (α-SMA). The levels of m6A modifications and related enzymes (Mettl3, Mettl14), Wilms tumor 1-associated protein (WTAP), fat mass and obesity protein (FTO), ALKBH5, YTHDF1, YTHDF2, YTHDC1, YTHDC2, YTHDC3 were assessed by Dot blot, RT-qPCR and Western blot. Mettl3 expression was inhibited in cells using lentivirus-mediated Mettl3-shRNA transfection, creating sh-Mettl3 and Ang Ⅱ+sh-Mettl3 groups, while lentivirus empty vector transfection served as the negative control (Ang Ⅱ+sh-NC group). The impact of Ang Ⅱ on pericyte transdifferentiation was observed, and the expression of downstream phosphatidylinositol 3-kinase (PI3K)/AKT signaling pathway proteins, including PI3K, AKT, phosphorylated AKT at serine 473 (p-AKT (S473)), and phosphorylated AKT at threonine 308 (p-AKT (T308)), were examined. PI3K gene transcription was inhibited by co-culturing cells with actinomycin D, and the half-life of PI3K mRNA was calculated by measuring residual PI3K mRNA expression over different co-culture time. The reversibility of Mettl3 inhibition on Ang Ⅱ-induced pericyte-to-myofibroblast transdifferentiation was assessed by adding the AKT activator SC79 to the Ang Ⅱ+sh-Mettl3 group. In animal experiments, mice were divided into these groups: sham group (administered 0.9% sterile saline), Ang Ⅱ group (infused with Ang Ⅱ solution), sh-Mettl3 group (injected with Mettl3 shRNA lentivirus solution), Ang Ⅱ+sh-Mettl3 group (infused with Ang Ⅱ solution and injected with Mettl3 shRNA lentivirus solution), and Ang Ⅱ+sh-Mettl3+SC79 group (administered Ang Ⅱ solution and Mettl3 shRNA lentivirus, with an additional injection of SC79). Each group consisted of six subject mice. Blood pressure was measured using the tail-cuff method before and after surgery, and serum creatinine, urea, and urinary albumin levels were determined 4 weeks post-surgery. Kidney tissues were collected at 28 days and stained using hematoxylin-eosin (HE) and Masson′s trichrome to assess the extent of renal fibrosis. Results:Primary renal pericytes were successfully obtained by magnetic bead sorting, and intervened with 1×10 6 mmol/L Ang Ⅱ for 48 hours to induce pericyte-to-myofibroblast transdifferentiation. Dot blot results indicated higher m6A modification levels in the Ang Ⅱ group compared to the control group ( P<0.05). RT-qPCR and Western blot results showed upregulation of Mettl3 mRNA and protein levels in the Ang Ⅱ group compared to the control group (both P<0.05). In the Ang Ⅱ+sh-Mettl3 group, Mettl3 protein expression was lower than that in the Ang Ⅱ group, with reduced expression levels of α-SMA, vimentin, desmin, fibroblast agonist protein (FAPa) and type Ⅰ collagen (all P<0.05). Compared to the control group, PI3K mRNA expression level was elevated in the Ang Ⅱ group, along with increased p-AKT (S473) and p-AKT (T308) expressions. In the Ang Ⅱ+sh-Mettl3 group, PI3K mRNA expression and p-AKT (S473) and p-AKT (T308) levels were decreased (all P<0.05). The half-life of PI3K mRNA was shorter in the Ang Ⅱ+sh-Mettl3 group than that in the Ang Ⅱ+sh-NC group (2.34 h vs. 3.42 h). The ameliorative effect of Mettl3 inhibition on Ang Ⅱ-induced pericyte-to-myofibroblast transdifferentiation was reversible by SC79. Animal experiments showed higher blood pressure, serum creatinine, urea, and 24-hour urinary protein levels, and a larger fibrosis area in the Ang Ⅱ group compared to the sham group (all P<0.05). The fibrosis area was smaller in the Ang Ⅱ+sh-Mettl3 group than that in the Ang Ⅱ group ( P<0.05), but increased again upon addition of SC79. Conclusion:Mettl3-mediated RNA m6A epigenetic regulation is involved in Ang Ⅱ-induced pericyte-to-myofibroblast transdifferentiation and renal fibrosis, potentially by affecting PI3K stability and regulating the PI3K/AKT signaling pathway.