Objective:To investigate the difference in brain activity intensity between methamphetamine (MA) dependent patients (MA group) and healthy controls (control group) using fractional amplitude of low-frequency fluctuation (fALFF), and to establish a classification model between these two groups using support vector machine (SVM).Methods:From February 2014 to October 2019, a total of 46 male MA-dependent patients and 46 male healthy controls were recruited from the Affiliated Kangning Hospital of Ningbo University. The study collected resting-state functional magnetic resonance imaging (rs-fMRI) data and analyzed the differences in brain functional activity between the two groups. This analysis was conducted using both static and dynamic fractional amplitude of low-frequency fluctuations (d-fALFF). Additionally, the study examined the correlation between fALFF/d-fALFF values in specific brain regions and the total scores, as well as each factor score, of the Brief Psychiatric Rating Scale (BPRS). Furthermore, the relationship between fALFF/d-fALFF values and the age of first use and total dose of MA in the MA group was investigated. Finally, the fALFF map and d-fALFF map of brain regions with significant differences between groups were used as features for constructing classification.Results:Compared to the healthy control group, those dependent on MA showed significantly increased fALFF mainly in the nucleus accumbens, caudate nucleus, thalamus, and amygdala nucleus( t=-5.21--2.72, all P<0.05). The MA group exhibited decreased fALFF in the superior frontal gyrus, middle frontal gyrus, orbital gyrus, and cingulate gyrus( t=3.59-5.00, all P<0.05). Most of the brain regions with decreased d-fALFF overlapped with those exhibiting decreased fALFF( t=3.33-4.87, all P<0.05). The results of the correlation analysis showed that the fALFF value of the right nucleus accumbens was positively correlated with the age of first use of MA ( r=0.537, P<0.001). There is no significant relationship between the abnormal fALFF and d-fALFF values in the MA group and the total scores and each factor scores of BPRS, as well as the total dose of MA taken (after removing outliers). Based on fALFF and d-fALFF values, the SVM classifier achieved accuracies of 90.33%±6.89% and 71.56%±7.80%, respectively. Conclusions:There are significant abnormalities in the low-frequency fluctuation of the resting brain in patients dependent on MA. These abnormalities reflect the rigidity of prefrontal cortex activity, functional impairment, and dysfunction of the anti-reward system. These factors may be one of the causes for MA dependent behavior and repeated episodes. In addition, the fALFF values may be helpful for distinguishing MA dependent individuals from the control group.

Allergic diseases,also known as hypersensitivity diseases,are a systemic disorder affecting nearly 40%of the global population.Although they vary in affected sites and clinical manifestations,they share many common features.For example,allergic diseases are the same type Ⅰ hypersensitivity reaction;the disease mechanism is based on the inability of the positive deficiency to resist the evil,and the allergens induce the onset of the disease;the course of the disease is similar to the patient's physique;the onset of the disease is closely related to the taiyin meridian of the hand and the foot;and the disease locations in traditional Chinese medicine can be categorized as the"orifices",so that the different diseases can be treated with the same treatment.Chinese medicine believes that spleen deficiency is the initiating factor of immune dysfunction,and lung deficiency is the key to the occurrence of allergic diseases,and regulating the lung and spleen is the key point of treatment for allergic diseases.The method of"cultivating the earth and generating gold"is good at adjusting the spleen and stomach and restoring the function of the lungs,which is the key to"same treatment for different diseases"of allergic diseases.Therefore,the purpose of this article is to explore the commonalities of allergic diseases and the role of the method of"cultivating the earth and generating gold"in the treatment of allergic diseases under the perspective of"same treatment for different diseases".

Allergic diseases,also known as hypersensitivity diseases,are a systemic disorder affecting nearly 40%of the global population.Although they vary in affected sites and clinical manifestations,they share many common features.For example,allergic diseases are the same type Ⅰ hypersensitivity reaction;the disease mechanism is based on the inability of the positive deficiency to resist the evil,and the allergens induce the onset of the disease;the course of the disease is similar to the patient's physique;the onset of the disease is closely related to the taiyin meridian of the hand and the foot;and the disease locations in traditional Chinese medicine can be categorized as the"orifices",so that the different diseases can be treated with the same treatment.Chinese medicine believes that spleen deficiency is the initiating factor of immune dysfunction,and lung deficiency is the key to the occurrence of allergic diseases,and regulating the lung and spleen is the key point of treatment for allergic diseases.The method of"cultivating the earth and generating gold"is good at adjusting the spleen and stomach and restoring the function of the lungs,which is the key to"same treatment for different diseases"of allergic diseases.Therefore,the purpose of this article is to explore the commonalities of allergic diseases and the role of the method of"cultivating the earth and generating gold"in the treatment of allergic diseases under the perspective of"same treatment for different diseases".

Objective:To investigate the difference in brain activity intensity between methamphetamine (MA) dependent patients (MA group) and healthy controls (control group) using fractional amplitude of low-frequency fluctuation (fALFF), and to establish a classification model between these two groups using support vector machine (SVM).Methods:From February 2014 to October 2019, a total of 46 male MA-dependent patients and 46 male healthy controls were recruited from the Affiliated Kangning Hospital of Ningbo University. The study collected resting-state functional magnetic resonance imaging (rs-fMRI) data and analyzed the differences in brain functional activity between the two groups. This analysis was conducted using both static and dynamic fractional amplitude of low-frequency fluctuations (d-fALFF). Additionally, the study examined the correlation between fALFF/d-fALFF values in specific brain regions and the total scores, as well as each factor score, of the Brief Psychiatric Rating Scale (BPRS). Furthermore, the relationship between fALFF/d-fALFF values and the age of first use and total dose of MA in the MA group was investigated. Finally, the fALFF map and d-fALFF map of brain regions with significant differences between groups were used as features for constructing classification.Results:Compared to the healthy control group, those dependent on MA showed significantly increased fALFF mainly in the nucleus accumbens, caudate nucleus, thalamus, and amygdala nucleus( t=-5.21--2.72, all P<0.05). The MA group exhibited decreased fALFF in the superior frontal gyrus, middle frontal gyrus, orbital gyrus, and cingulate gyrus( t=3.59-5.00, all P<0.05). Most of the brain regions with decreased d-fALFF overlapped with those exhibiting decreased fALFF( t=3.33-4.87, all P<0.05). The results of the correlation analysis showed that the fALFF value of the right nucleus accumbens was positively correlated with the age of first use of MA ( r=0.537, P<0.001). There is no significant relationship between the abnormal fALFF and d-fALFF values in the MA group and the total scores and each factor scores of BPRS, as well as the total dose of MA taken (after removing outliers). Based on fALFF and d-fALFF values, the SVM classifier achieved accuracies of 90.33%±6.89% and 71.56%±7.80%, respectively. Conclusions:There are significant abnormalities in the low-frequency fluctuation of the resting brain in patients dependent on MA. These abnormalities reflect the rigidity of prefrontal cortex activity, functional impairment, and dysfunction of the anti-reward system. These factors may be one of the causes for MA dependent behavior and repeated episodes. In addition, the fALFF values may be helpful for distinguishing MA dependent individuals from the control group.

AIM: To investigate the clinical features of acute exacerbation chronic obstructive pulmonary disease (AECOPD) of complicated with type 2 diabetes mellitus (T2DM), and analyze the related clinical features and risk factors. METHODS: This was a single-center cross-sectional study. From March 2020 to January 2023, 479 hospitalized patients with AECOPD in the department of respiratory and critical care medicine, Suining Central Hospital were included. There were 215 patients in AECOPD group and 60 patients in AECOPD with T2DM group. The collected variables included demographic data, complications, blood routine, infection index, random blood glucose, blood gas analysis and lung function. The adoption rate and constituent ratio of the basic description classification data were expressed as mean standard deviation for the normal distribution measurement data and median interquartile range for the skew distribution measurement data. T-test was used for normal distribution and non - parameter test was used for non-normal distribution. The categorical variables were tested by chi-square test. Rank sum test was used for rank variable data. Binary logistic regression model was used to investigate the independent factors associated with T2DM in patients with AECOPD. Finally, the results of logistic regression were verified and visualized by nomogram, validation curve, ROC curve and DCA curve. P<0.05 was a significant statistical difference. RESULTS: Univariate analysis showed that there were significant differences in body mass index (BMI), essential hypertension, coronary heart disease, atrial fibrillation (AF), pulmonary function (GOLD stage), blood neutrophil (NS), blood lymphocyte (LYM), arterial blood gas PaCO2, Alanine transaminase (ALT) and random blood glucose (RBG) between the two groups (P<0.05). The binary logistic regression model (C-index=0.847) was constructed with the above 10 variables, the results showed that BMI (OR=1.309), Af (OR= 8.188), LYM counts (OR=0.474), PaCO2 (OR=1.082) and RBG (OR=1.434) were independently associated with type 2 diabetes in patients with AECOPD (all P>0.05). The results of logistic regression were verified and visualized by Nomogram and its-associated ccurves. The MAE and AUC curves were 0.021 and 0.847 respectively, indicating that the model had good prediction consistency and accuracy. The DCA curve showed that Nomogram's risk threshold ranged from 0.01 to 0.99, suggesting that nomogram's model had better clinical predictive value. CONCLUSION: Our results showed that increased BMI, PaCO2 and random glucose, decreased blood lymphocyte, and atrial fibrillation is an independent clinical feature of AECOPD with T2DM. These results suggest that the immune function of patients with AECOPD and T2DM are more severely impaired and more likely to be accompanied by atrial fibrillation, which is a potential cause of poor prognosis in these patients. Meanwhile, this conclusion needs to be further verified in multicenter study with large sample size.

AIM:To investigate the clinical fea-tures of acute exacerbation chronic obstructive pul-monary disease(AECOPD)of complicated with type 2 diabetes mellitus(T2DM),and analyze the relat-ed clinical features and risk factors.METHODS:This was a single-center cross-sectional study.From March 2020 to January 2023,479 hospitalized pa-tients with AECOPD in the department of respirato-ry and critical care medicine,Suining Central Hospi-tal were included.There were 215 patients in AE-COPD group and 60 patients in AECOPD with T2DM group.The collected variables included demograph-ic data,complications,blood routine,infection in-dex,random blood glucose,blood gas analysis and lung function.The adoption rate and constituent ra-tio of the basic description classification data were expressed as mean standard deviation for the nor-mal distribution measurement data and median in-terquartile range for the skew distribution measure-ment data.T-test was used for normal distribution and non-parameter test was used for non-normal distribution.The categorical variables were tested by chi-square test.Rank sum test was used for rank variable data.Binary logistic regression model was used to investigate the independent factors associ-ated with T2DM in patients with AECOPD.Finally,the results of logistic regression were verified and visualized by nomogram,validation curve,ROC curve and DCA curve.P＜0.05 was a significant sta-tistical difference.RESULTS:Univariate analysis showed that there were significant differences in body mass index(BMI),essential hypertension,cor-onary heart disease,atrial fibrillation(AF),pulmo-nary function(GOLD stage),blood neutrophil(NS),blood lymphocyte(LYM),arterial blood gas PaCO2,Alanine transaminase(ALT)and random blood glu-cose(RBG)between the two groups(P＜0.05).The binary logistic regression model(C-index=0.847)was constructed with the above 10 variables,the results showed that BMI(OR=1.309),Af(OR=8.188),LYM counts(OR=0.474),PaCO2(OR=1.082)and RBG(OR=1.434)were independently associat-ed with type 2 diabetes in patients with AECOPD(all P＞0.05).The results of logistic regression were verified and visualized by Nomogram and its-associ-ated ccurves.The MAE and AUC curves were 0.021 and 0.847 respectively,indicating that the model had good prediction consistency and accuracy.The DCA curve showed that Nomogram's risk threshold ranged from 0.01 to 0.99,suggesting that nomo-gram's model had better clinical predictive value.CONCLUSION:Our results showed that increased BMI,PaCO2 and random glucose,decreased blood lymphocyte,and atrial fibrillation is an indepen-dent clinical feature of AECOPD with T2DM.These results suggest that the immune function of pa-tients with AECOPD and T2DM are more severely impaired and more likely to be accompanied by atrial fibrillation,which is a potential cause of poor prognosis in these patients.Meanwhile,this conclu-sion needs to be further verified in multicenter study with large sample size.

AIM:To investigate the clinical fea-tures of acute exacerbation chronic obstructive pul-monary disease(AECOPD)of complicated with type 2 diabetes mellitus(T2DM),and analyze the relat-ed clinical features and risk factors.METHODS:This was a single-center cross-sectional study.From March 2020 to January 2023,479 hospitalized pa-tients with AECOPD in the department of respirato-ry and critical care medicine,Suining Central Hospi-tal were included.There were 215 patients in AE-COPD group and 60 patients in AECOPD with T2DM group.The collected variables included demograph-ic data,complications,blood routine,infection in-dex,random blood glucose,blood gas analysis and lung function.The adoption rate and constituent ra-tio of the basic description classification data were expressed as mean standard deviation for the nor-mal distribution measurement data and median in-terquartile range for the skew distribution measure-ment data.T-test was used for normal distribution and non-parameter test was used for non-normal distribution.The categorical variables were tested by chi-square test.Rank sum test was used for rank variable data.Binary logistic regression model was used to investigate the independent factors associ-ated with T2DM in patients with AECOPD.Finally,the results of logistic regression were verified and visualized by nomogram,validation curve,ROC curve and DCA curve.P＜0.05 was a significant sta-tistical difference.RESULTS:Univariate analysis showed that there were significant differences in body mass index(BMI),essential hypertension,cor-onary heart disease,atrial fibrillation(AF),pulmo-nary function(GOLD stage),blood neutrophil(NS),blood lymphocyte(LYM),arterial blood gas PaCO2,Alanine transaminase(ALT)and random blood glu-cose(RBG)between the two groups(P＜0.05).The binary logistic regression model(C-index=0.847)was constructed with the above 10 variables,the results showed that BMI(OR=1.309),Af(OR=8.188),LYM counts(OR=0.474),PaCO2(OR=1.082)and RBG(OR=1.434)were independently associat-ed with type 2 diabetes in patients with AECOPD(all P＞0.05).The results of logistic regression were verified and visualized by Nomogram and its-associ-ated ccurves.The MAE and AUC curves were 0.021 and 0.847 respectively,indicating that the model had good prediction consistency and accuracy.The DCA curve showed that Nomogram's risk threshold ranged from 0.01 to 0.99,suggesting that nomo-gram's model had better clinical predictive value.CONCLUSION:Our results showed that increased BMI,PaCO2 and random glucose,decreased blood lymphocyte,and atrial fibrillation is an indepen-dent clinical feature of AECOPD with T2DM.These results suggest that the immune function of pa-tients with AECOPD and T2DM are more severely impaired and more likely to be accompanied by atrial fibrillation,which is a potential cause of poor prognosis in these patients.Meanwhile,this conclu-sion needs to be further verified in multicenter study with large sample size.

AIM:To investigate the clinical fea-tures of acute exacerbation chronic obstructive pul-monary disease(AECOPD)of complicated with type 2 diabetes mellitus(T2DM),and analyze the relat-ed clinical features and risk factors.METHODS:This was a single-center cross-sectional study.From March 2020 to January 2023,479 hospitalized pa-tients with AECOPD in the department of respirato-ry and critical care medicine,Suining Central Hospi-tal were included.There were 215 patients in AE-COPD group and 60 patients in AECOPD with T2DM group.The collected variables included demograph-ic data,complications,blood routine,infection in-dex,random blood glucose,blood gas analysis and lung function.The adoption rate and constituent ra-tio of the basic description classification data were expressed as mean standard deviation for the nor-mal distribution measurement data and median in-terquartile range for the skew distribution measure-ment data.T-test was used for normal distribution and non-parameter test was used for non-normal distribution.The categorical variables were tested by chi-square test.Rank sum test was used for rank variable data.Binary logistic regression model was used to investigate the independent factors associ-ated with T2DM in patients with AECOPD.Finally,the results of logistic regression were verified and visualized by nomogram,validation curve,ROC curve and DCA curve.P＜0.05 was a significant sta-tistical difference.RESULTS:Univariate analysis showed that there were significant differences in body mass index(BMI),essential hypertension,cor-onary heart disease,atrial fibrillation(AF),pulmo-nary function(GOLD stage),blood neutrophil(NS),blood lymphocyte(LYM),arterial blood gas PaCO2,Alanine transaminase(ALT)and random blood glu-cose(RBG)between the two groups(P＜0.05).The binary logistic regression model(C-index=0.847)was constructed with the above 10 variables,the results showed that BMI(OR=1.309),Af(OR=8.188),LYM counts(OR=0.474),PaCO2(OR=1.082)and RBG(OR=1.434)were independently associat-ed with type 2 diabetes in patients with AECOPD(all P＞0.05).The results of logistic regression were verified and visualized by Nomogram and its-associ-ated ccurves.The MAE and AUC curves were 0.021 and 0.847 respectively,indicating that the model had good prediction consistency and accuracy.The DCA curve showed that Nomogram's risk threshold ranged from 0.01 to 0.99,suggesting that nomo-gram's model had better clinical predictive value.CONCLUSION:Our results showed that increased BMI,PaCO2 and random glucose,decreased blood lymphocyte,and atrial fibrillation is an indepen-dent clinical feature of AECOPD with T2DM.These results suggest that the immune function of pa-tients with AECOPD and T2DM are more severely impaired and more likely to be accompanied by atrial fibrillation,which is a potential cause of poor prognosis in these patients.Meanwhile,this conclu-sion needs to be further verified in multicenter study with large sample size.

AIM:To investigate the clinical fea-tures of acute exacerbation chronic obstructive pul-monary disease(AECOPD)of complicated with type 2 diabetes mellitus(T2DM),and analyze the relat-ed clinical features and risk factors.METHODS:This was a single-center cross-sectional study.From March 2020 to January 2023,479 hospitalized pa-tients with AECOPD in the department of respirato-ry and critical care medicine,Suining Central Hospi-tal were included.There were 215 patients in AE-COPD group and 60 patients in AECOPD with T2DM group.The collected variables included demograph-ic data,complications,blood routine,infection in-dex,random blood glucose,blood gas analysis and lung function.The adoption rate and constituent ra-tio of the basic description classification data were expressed as mean standard deviation for the nor-mal distribution measurement data and median in-terquartile range for the skew distribution measure-ment data.T-test was used for normal distribution and non-parameter test was used for non-normal distribution.The categorical variables were tested by chi-square test.Rank sum test was used for rank variable data.Binary logistic regression model was used to investigate the independent factors associ-ated with T2DM in patients with AECOPD.Finally,the results of logistic regression were verified and visualized by nomogram,validation curve,ROC curve and DCA curve.P＜0.05 was a significant sta-tistical difference.RESULTS:Univariate analysis showed that there were significant differences in body mass index(BMI),essential hypertension,cor-onary heart disease,atrial fibrillation(AF),pulmo-nary function(GOLD stage),blood neutrophil(NS),blood lymphocyte(LYM),arterial blood gas PaCO2,Alanine transaminase(ALT)and random blood glu-cose(RBG)between the two groups(P＜0.05).The binary logistic regression model(C-index=0.847)was constructed with the above 10 variables,the results showed that BMI(OR=1.309),Af(OR=8.188),LYM counts(OR=0.474),PaCO2(OR=1.082)and RBG(OR=1.434)were independently associat-ed with type 2 diabetes in patients with AECOPD(all P＞0.05).The results of logistic regression were verified and visualized by Nomogram and its-associ-ated ccurves.The MAE and AUC curves were 0.021 and 0.847 respectively,indicating that the model had good prediction consistency and accuracy.The DCA curve showed that Nomogram's risk threshold ranged from 0.01 to 0.99,suggesting that nomo-gram's model had better clinical predictive value.CONCLUSION:Our results showed that increased BMI,PaCO2 and random glucose,decreased blood lymphocyte,and atrial fibrillation is an indepen-dent clinical feature of AECOPD with T2DM.These results suggest that the immune function of pa-tients with AECOPD and T2DM are more severely impaired and more likely to be accompanied by atrial fibrillation,which is a potential cause of poor prognosis in these patients.Meanwhile,this conclu-sion needs to be further verified in multicenter study with large sample size.

AIM:To investigate the clinical fea-tures of acute exacerbation chronic obstructive pul-monary disease(AECOPD)of complicated with type 2 diabetes mellitus(T2DM),and analyze the relat-ed clinical features and risk factors.METHODS:This was a single-center cross-sectional study.From March 2020 to January 2023,479 hospitalized pa-tients with AECOPD in the department of respirato-ry and critical care medicine,Suining Central Hospi-tal were included.There were 215 patients in AE-COPD group and 60 patients in AECOPD with T2DM group.The collected variables included demograph-ic data,complications,blood routine,infection in-dex,random blood glucose,blood gas analysis and lung function.The adoption rate and constituent ra-tio of the basic description classification data were expressed as mean standard deviation for the nor-mal distribution measurement data and median in-terquartile range for the skew distribution measure-ment data.T-test was used for normal distribution and non-parameter test was used for non-normal distribution.The categorical variables were tested by chi-square test.Rank sum test was used for rank variable data.Binary logistic regression model was used to investigate the independent factors associ-ated with T2DM in patients with AECOPD.Finally,the results of logistic regression were verified and visualized by nomogram,validation curve,ROC curve and DCA curve.P＜0.05 was a significant sta-tistical difference.RESULTS:Univariate analysis showed that there were significant differences in body mass index(BMI),essential hypertension,cor-onary heart disease,atrial fibrillation(AF),pulmo-nary function(GOLD stage),blood neutrophil(NS),blood lymphocyte(LYM),arterial blood gas PaCO2,Alanine transaminase(ALT)and random blood glu-cose(RBG)between the two groups(P＜0.05).The binary logistic regression model(C-index=0.847)was constructed with the above 10 variables,the results showed that BMI(OR=1.309),Af(OR=8.188),LYM counts(OR=0.474),PaCO2(OR=1.082)and RBG(OR=1.434)were independently associat-ed with type 2 diabetes in patients with AECOPD(all P＞0.05).The results of logistic regression were verified and visualized by Nomogram and its-associ-ated ccurves.The MAE and AUC curves were 0.021 and 0.847 respectively,indicating that the model had good prediction consistency and accuracy.The DCA curve showed that Nomogram's risk threshold ranged from 0.01 to 0.99,suggesting that nomo-gram's model had better clinical predictive value.CONCLUSION:Our results showed that increased BMI,PaCO2 and random glucose,decreased blood lymphocyte,and atrial fibrillation is an indepen-dent clinical feature of AECOPD with T2DM.These results suggest that the immune function of pa-tients with AECOPD and T2DM are more severely impaired and more likely to be accompanied by atrial fibrillation,which is a potential cause of poor prognosis in these patients.Meanwhile,this conclu-sion needs to be further verified in multicenter study with large sample size.