Smart diabetic foot ulcer scoring system.

Current assessment methods for diabetic foot ulcers (DFUs) lack objectivity and consistency, posing a significant risk to diabetes patients, including the potential for amputations, highlighting the urgent need for improved diagnostic tools and care standards in the field. To address this issue, the objective of this study was to develop and evaluate the Smart Diabetic Foot Ulcer Scoring System, ScoreDFUNet, which incorporates artificial intelligence (AI) and image analysis techniques, aiming to enhance the precision and consistency of diabetic foot ulcer assessment. ScoreDFUNet demonstrates precise categorization of DFU images into "ulcer," "infection," "normal," and "gangrene" areas, achieving a noteworthy accuracy rate of 95.34% on the test set, with elevated levels of precision, recall, and F1 scores. Comparative evaluations with dermatologists affirm that our algorithm consistently surpasses the performance of junior and mid-level dermatologists, closely matching the assessments of senior dermatologists, and rigorous analyses including Bland-Altman plots and significance testing validate the robustness and reliability of our algorithm. This innovative AI system presents a valuable tool for healthcare professionals and can significantly improve the care standards in the field of diabetic foot ulcer assessment.

Enhanced adsorption of phosphate by rice straw-based biochar prepared via metal impregnation and bio-template technology.

Phosphate removal from water through green, highly efficient technologies has received much attention. Biochar is an effective adsorbent for phosphate removal. However, adsorption capacity of phosphate on pristine rice straw-based biochar was not optimistic due to low anion exchange capacity. In this study, Fe-modified, Mg-modified and MgFe-modified rice straw-based biochar (Fe-BC, Mg-BC and MgFe-BC) were prepared by combining metal impregnation and biological template methods to improve the adsorption capacity of phosphate. The surface characteristics of biochar and the adsorption behavior of phosphate on biochar were investigated. The modified biochar had the specific surface area of 17.910-39.336 m2/g, and their surfaces were rich in a large number of functional groups and metal oxides. Phosphate release was observed on pristine rice straw-based biochar without metal impregnation. The maximum adsorption capacities of phosphate on MgFe-BC, Mg-BC and Fe-BC at 298 K were 6.93, 5.75 and 0.23 mg/g, respectively. Adsorption was a spontaneous endothermic process, while chemical adsorption dominated and electrostatic attraction and pores filling existed simultaneously. Based on the site energy distribution theory study, the standard deviation of MgFe-BC decreased from 6.96 to 4.64 kJ/mol with temperature increasing, which proved that the higher the temperature would cause the lower heterogeneity. Moreover, the effects of pH, humic acid, co-existing ions and ionic strength on phosphate adsorption of MgFe-BC were also discussed. MgFe-BC with fine pores and efficient adsorption sites is an ideal adsorbent for phosphate removal from water.

Application of a Diabetic Foot Smart APP in the measurement of diabetic foot ulcers.

AIMS: In the early stage, we developed an intelligent measurement APP for diabetic foot ulcers, named Diabetic Foot Smart APP. This study aimed to validate the APP in the measurement of ulcer area for diabetic foot ulcer (DFU). METHODS: We selected 150 DFU images to measure the ulcer areas using three assessment tools: the Smart APP software package, the ruler method, and the gold standard Image J software, and compared the measurement results and measurement time of the three tools. The intra-rater and inter-rater reliability were described by Pearson correlation coefficient, intra-group correlation coefficient, and coefficient of variation. RESULTS: The Image J software showed a median ulcer area of 4.02 cm2, with a mean measurement time of 66.37 ± 7.95 s. The ruler method showed a median ulcer area of 5.14 cm2, with a mean measurement time of 171.47 ± 46.43 s. The APP software showed a median ulcer area of 3.70 cm2, with a mean measurement time of 38.25 ± 6.81 s. There were significant differences between the ruler method and the golden standard Image J software (Z = -4.123, p < 0.05), but no significant difference between the APP software and the Image J software (Z = 1.103, p > 0.05). The APP software also showed good inter-rater reliability and intra-rater reliability, with both reaching 0.99. CONCLUSION: The Diabetic Foot Smart APP is a fast and reliable measurement tool with high measurement accuracy that can be easily used in clinical practice for the measurement of ulcer areas of DFU. TRIAL REGISTRATION: Chinese clinical trial registration number: ChiCTR2100047210.

Knowledge, attitudes, and practice of Endocrinology healthcare workers regarding screening for pre-ulcerative diabetic foot lesions.

OBJECTIVE: To investigate knowledge, attitude and practice of screening pre-ulcerative lesions among endocrinology healthcare workers. METHODS: A new questionnaire was developed and distributed online and 1004 valid questionnaires were returned. T-test, ANOVA, Pearson correlation analysis, and multiple linear regression were used for statistical analysis. RESULTS: A total of 1100 questionnaires were returned, and 96 were excluded. The scores of endocrinology healthcare workers' knowledge, attitude, and practice for screening for pre-ulcerative lesions were 45.46 ± 16.26, 92.11 ± 10.50, and 72.27 ± 17.63 respectively. 60.2% participants had been trained to screen for pre-ulcerative lesions, but 39.8% had not been trained. 31.8% of healthcare professionals claimed that their hospital did not have a screening project for pre-ulcer diabetic foot lesions. Positive relationships were found between knowledge and practice and between attitude and practice. Multiple linear regression analysis showed that: level II hospital and tertiary hospital were the main factors influencing the knowledge scores; Undergraduate and participating in relevant training were the main factors influencing the attitude scores; participating in relevant training, hospital conducts relevant projects, and patient cooperation, and working hours were the main factors influencing the practice score. CONCLUSIONS: Endocrinology healthcare workers need more knowledge regarding pre-ulcerative lesions, and their screening practices need to be strengthened. Increased education and training for pre-ulcerative lesion screening should be implemented among healthcare workers in endocrinology departments.

The changes in iron ions concentration and organic matter composition during the surface microlayer membrane formation process in freshwater.

The surface microlayer membrane (SMM) is a complex and unique water body ecosystem. The SMM has a significant effect on water quality and the water ecological system. However, despite the long-lasting interest in the SMM formation process and its environmental effect mechanism in freshwater, studies on it are still scarce. This paper studied the changes in iron ions concentration and organic matter composition during the SMM formation process. Our results revealed that the iron ions enriched in the SMM, at a concentration of up to 8.02 µg/mL, exist in the form of Fe3+. The main organic matter is polysaccharides and proteins in the SMM. Additionally, the microbial community structure revealed that the changes in iron ion morphology in water and the SMM was a significant association with the presence of Aeromonas and Zoogloea. The rapid enrichment process of iron ions and organic matter in the aquatic surface microlayer is involved in the rapid formation of early SMM. Obviously, these findings provide new insights and a basis for the SMM of freshwater.

Gender differences in metabolic syndrome and its components in southern china using a healthy lifestyle index: a cross-sectional study.

BACKGROUND: Lifestyle changes are important for the prevention and management of metabolic syndrome (MetS), but studies that focus on gender differences in the lifestyle risk factors of MetS are limited in China. This research aimed to generate a healthy lifestyle index (HLI) to assess the behavioral risk factors of MetS and its components, and to explore the gender differences in HLI score and other influencing factors of MetS. METHODS: A convenience sample of 532 outpatients were recruited from a general hospital in Changsha, China. The general information and HLI scores [including physical activity (PA), diet, smoking, alcohol use, and body mass index (BMI)] of the subjects were collected through questionnaires, and each patient's height, weight, waist circumference, and other physical signs were measured. Logistic regression analysis was used to analyze the risk factors of MetS and its components. RESULTS: The prevalence of MetS was 33.3% for the whole sample (46.3% in males and 23.3% in females). The risk of MetS increased with age, smoking, unhealthy diet, and BMI in males and with age and BMI in females. Our logistic regression analysis showed that lower HLI (male: OR = 0.838,95%CI = 0.757-0.929; female: OR = 0.752, 95%CI = 0.645-0.876) and older age (male: OR = 2.899, 95%CI = 1.446-5.812; female: OR = 4.430, 95%CI = 1.640-11.969) were independent risk factors of MetS, for both sexes. CONCLUSION: Low levels of HLI and older ages were independent risk factors of MetS in both males and females. The association between aging and MetS risk was stronger in females, while the association between unhealthy lifestyles and MetS risk was stronger in males. Our findings reinforced the expected gender differences in MetS prevalence and its risk factors, which has implications for the future development of gender-specific MetS prevention and intervention programs.

Screening behaviors for diabetic foot risk and their influencing factors among general practitioners: a cross-sectional study in Changsha, China.

BACKGROUND: Diabetic foot is a serious complication of diabetes with a high disability and mortality rate, which can be prevented by early screening. General practitioners play an essential role in diabetic foot risk screening, yet the screening behaviors of general practitioners have rarely been studied in primary care settings. This study aimed to investigate foot risk screening behaviors and analyze their influencing factors among general practitioners. METHODS: A cross-sectional study was conducted among 844 general practitioners from 78 community health centers in Changsha, China. A self-designed and validated questionnaire was used to assess the general practitioner's cognition, attitude, and behaviors on performing diabetic foot risk screening. Multivariate linear regression was conducted to investigate the influencing factors of risk screening behaviors. RESULTS: The average score of diabetic foot risk screening behaviors among the general practitioners was 61.53 ± 14.69, and 271 (32.1%) always or frequently performed foot risk screening for diabetic patients. Higher training frequency (ß = 3.197, p < 0.001), higher screening cognition (ß = 2.947, p < 0.001), and more positive screening attitude (ß = 4.564, p < 0.001) were associated with more diabetic foot risk screening behaviors, while limited time and energy (ß=-5.184, p < 0.001) and lack of screening tools (ß=-6.226, p < 0.001) were associated with fewer diabetic foot screening behaviors. CONCLUSION: The score of risk screening behaviors for the diabetic foot of general practitioners in Changsha was at a medium level. General practitioners' diabetic foot risk screening behaviors may be improved through strengthening training on relevant guidelines and evidence-based screening techniques, improving cognition and attitude towards foot risk screening among general practitioners, provision of more general practitioners or nurse practitioners, and user-friendly screening tools.

A comprehensive review of methods based on deep learning for diabetes-related foot ulcers.

Background: Diabetes mellitus (DM) is a chronic disease with hyperglycemia. If not treated in time, it may lead to lower limb amputation. At the initial stage, the detection of diabetes-related foot ulcer (DFU) is very difficult. Deep learning has demonstrated state-of-the-art performance in various fields and has been used to analyze images of DFUs. Objective: This article reviewed current applications of deep learning to the early detection of DFU to avoid limb amputation or infection. Methods: Relevant literature on deep learning models, including in the classification, object detection, and semantic segmentation for images of DFU, published during the past 10 years, were analyzed. Results: Currently, the primary uses of deep learning in early DFU detection are related to different algorithms. For classification tasks, improved classification models were all based on convolutional neural networks (CNNs). The model with parallel convolutional layers based on GoogLeNet and the ensemble model outperformed the other models in classification accuracy. For object detection tasks, the models were based on architectures such as faster R-CNN, You-Only-Look-Once (YOLO) v3, YOLO v5, or EfficientDet. The refinements on YOLO v3 models achieved an accuracy of 91.95% and the model with an adaptive faster R-CNN architecture achieved a mean average precision (mAP) of 91.4%, which outperformed the other models. For semantic segmentation tasks, the models were based on architectures such as fully convolutional networks (FCNs), U-Net, V-Net, or SegNet. The model with U-Net outperformed the other models with an accuracy of 94.96%. Taking segmentation tasks as an example, the models were based on architectures such as mask R-CNN. The model with mask R-CNN obtained a precision value of 0.8632 and a mAP of 0.5084. Conclusion: Although current research is promising in the ability of deep learning to improve a patient's quality of life, further research is required to better understand the mechanisms of deep learning for DFUs.

Health Economic Indicators in Patients With Diabetic Foot: Outpatient Multidisciplinary Management.

The purpose of this study is to investigate the influence of an outpatient multidisciplinary diagnosis and treatment model on the health economic indices of diabetic foot patients. We included 142 diabetic foot patients who received treatment in 2 target hospitals from January to April 2018 in this prospective cohort study. According to their exposure factors, the patients were divided into a MDT group and a control group, with 71 patients in each group. The patients' baseline data were collected. The follow-up period was 12 months; all patients were followed up to April 30, 2019. Health economic indicators were collected when the patients were discharged from the hospital. The prognosis of each group was followed every month. If a wound healed, a major amputation occurred, or the patient died within 12 months, the follow-up was stopped. A total of 129 patients were followed, and their baseline data were comparable. During the follow-up period, the healing rate of the 2 groups was significantly different (P = .034). The healing rate of Wagner grade 4 patients was significantly better than Wagner grade 2 and grade 3 patients (P = .001). Health economic indicators demonstrated significant differences in bed waiting time (P = .038), transfer time (P = .001), surgery waiting time (P = .003), length of hospital stay (P = .047), and hospitalization expenses (P = .011). In conclusion, an outpatient multidisciplinary diagnosis and treatment model for diabetic foot can support cost-effective patient management.

The actuality of resilience, social support and quality of life among patients with inflammatory bowel disease in China.

AIM: This study was conducted to increase knowledge on the actuality of resilience, social support and quality of life among inflammatory bowel disease patients in China to provide evidence for psychological support. DESIGN: Using convenience sampling, 249 outpatients and inpatients with inflammatory bowel disease from a hospital who completed the questionnaires were enrolled in the analytic questionnaire-based study. METHODS: Demographic information forms, Resilience Scale for Inflammatory Bowel Disease, Social Support Rating Scale and Short Health Scale were administered. RESULTS: It was found that the resilience of patients with inflammatory bowel disease should be enhanced. When considering factors that influence resilience, the place of residence (living in rural areas) and utilization of social support should be considered. Resilience demonstrated a positive correlation with utilization of social support, and different place of residence was related to resilience. Targeted interventions should be implemented to increase patients' resilience and quality of life.

Construction and verification of an intelligent measurement model for diabetic foot ulcer. / ä¸€ç§ç³–å°¿ç— è¶³æºƒç–¡æ™ºèƒ½æµ‹é‡æ¨¡åž‹çš„æž„å»ºä¸ŽéªŒè¯.

OBJECTIVES: The measurement of diabetic foot ulcers is important for the success in diabetic foot ulcer management. At present, it lacks the accurate and convenient measurement tools in clinical. In recent years, artificial intelligence technology has demonstrated the potential application value in the field of image segmentation and recognition. This study aims to construct an intelligent measurement model of diabetic foot ulcers based on the deep learning method, and to conduct preliminary verification. METHODS: The data of 1 042 diabetic foot ulcers clinical samples were collected. The ulcers and color areas were manually labeled, of which 782 were used as the training data set and 260 as the test data set. The Mask RCNN ulcer tissue color semantic segmentation and RetinaNet scale digital scale target detection were used to build a model. The training data set was input into the model and iterated. The test data set was used to verify the intelligent measurement model. RESULTS: This study established an intelligent measurement model of diabetic foot ulcers based on deep learning. The mean average precision@.5 intersection over union (mAP@.5IOU) of the color region segmentation in the training set and the test set were 87.9% and 63.9%, respectively; the mAP@.5IOU of the ruler scale digital detection in the training set and the test set were 96.5% and 83.4%, respectively. Compared with the manual measurement result of the test sample, the average error of the intelligent measurement result was about 3 mm. CONCLUSIONS: The intelligent measurement model has good accuracy and robustness in measuring the diabetic foot ulcers. Future research can further optimize the model with larger-scale data samples.

Application of the Ipswich Touch Test for diabetic peripheral neuropathy screening: a systematic review and meta-analysis.

OBJECTIVE: Diabetic peripheral neuropathy (DPN) is one of the most important risk factors of diabetic foot ulcers, and early screening and treatment of DPN are crucial. The Ipswich Touch Test (IPTT) is a new method for screening for DPN and, compared with traditional methods, is more simple to operate and requires no equipment. However, the screening accuracy of IPTT in patients with DPN has not been well characterised. We aim to conduct a systematic review and meta-analysis to characterise the sensitivity and specificity of IPTT compared with traditional methods and to understand the potential screening value of IPTT. DESIGN: Systematic review and meta-analysis. DATA SOURCES: PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure, Wanfang, Chinese Biomedical Literature Database up to 16 April 2020. METHODS: Stata V.15.1 software was used for analysis, and the screening value of IPTT in DPN was described using 10 g monofilament (10g-MF), neuropathy disability scores (NDS), Pin prick, 128 Hz tuning fork, and ankle reflex as reference standards. Sensitivity, specificity and other measures of accuracy of IPTT for screening DPN were pooled based on a quality effects model. The protocol was registered with PROSPERO (42020168420). RESULTS: Of the 441 records retrieved, 7 studies were evaluated for the screening value of IPTT. Five studies with 10g-MF as the reference standard were included in the meta-analysis, and the pooled sensitivity and specificity were 0.77 (95％CI 0.69-0.84) and 0.96(95％CI 0.93-0.98), respectively, and the area under curve was 0.897. Compared with vibration perception threshold, IPTT showed a sensitivity between 0.76 and 1, and a specificity between 0.90 and 0.97. Compared with NDS, IPTT showed a sensitivity between 0.53 and 1, and a specificity between 0.90 and 0.97. Compared with Pin prick, IPTT showed a sensitivity and specificity of 0.8 and 0.88, respectively. Compared with 128 Hz tuning fork, IPTT showed a sensitivity and specificity of 0.4 and 0.27, respectively. Compared with ankle reflex, IPTT had a sensitivity of 0.2 and a specificity of 0.97. CONCLUSIONS: IPTT shows a high degree of agreement with other commonly used screening tools for DPN screening. It can be used clinically, especially in remote areas and in primary medical institutions, and by self-monitoring patients. More high-quality studies are needed to assess and promote more effective screening practices. PROSPERO REGISTRATION NUMBER: Registration Number is CRD (42020168420).

Integrated analysis of tRNA-derived small RNAs reveals new therapeutic genes of hyperbaric oxygen in diabetic foot ulcers.

Background: To reveal the alterations of tRNA-derived small RNA (tsRNA) expression profiles induced by hyperbaric oxygen (HBO) treatment in diabetic foot ulcers (DFUs) and investigate new therapeutic targets. Materials & methods: tsRNA sequencing was employed in normal skin tissue, in DFUs, and after HBO treatment groups. A quantitative real-time PCR was used to validate tsRNA sequencing results and their targets levels. Bioinformatics analysis was performed to reveal their therapeutic functions in DFUs. Results: A total of 22 tsRNAs were differentially expressed in the three groups. Three selected tsRNAs were validated by quantitative real-time PCR for further analysis, which were all significantly overexpressed in DFU while being normally expressed after HBO treatment. Bioinformatics analysis disclosed that these tsRNAs may play therapeutic roles through the regulation of the Wnt signaling pathway. Conclusion: tsRNAs may be novel useful targets for HBO to treat DFUs.

Sleep Quality in Medical Staffs During the Outbreak of Coronavirus Disease 2019 in China: A Web-Based Cross-Sectional Study.

Background: The aim of this study was to describe the sleep quality and its influencing factors among medical workers of different working statuses and staff types during the coronavirus disease 2019 (COVID-19) epidemic. Methods: Through an online questionnaire survey, all medical staffs in Xiangya Hospital were invited to complete sections on general information, the Self-Rating Scale of Sleep (SRSS), the Depression, Anxiety and Stress Scale (DASS-21), the Social Support Rating Scale (SSRS), and the Simplified Coping Style Questionnaire (CSQ). Results: A total of 4,245 respondents completed the survey. Among them, 38.7% had sleep disturbance. After matching, the SRSS scores in the staffs who were assigned to the intensive care unit (ICU) of Union Hospital in Wuhan and working in the epidemic area of Xiangya Hospital were not significantly different (P > 0.05); the SRSS scores in the battlefront staffs were significantly higher than (P < 0.05) those who were not treating patients infected with COVID-19. The SRSS scores of nurses were significantly higher than those of doctors and hospital administrators (P < 0.01). Anxiety, depression, and coping style were associated with sleep disturbance. Conclusion: The sleep quality of the medical staffs has been impaired during the epidemic period, especially among nurses, doctors, and administrators who are working on the front line. Medical institutions should strengthen psychological services and coping strategies for medical staffs.

Psychological status of the staff in a general hospital during the outbreak of coronavirus disease 2019 and its influential factors. / 2019å† çŠ¶ç— æ¯’ç— ç–«æƒ æœŸé—´æŸç»¼åˆåŒ»é™¢å‘˜å·¥çš„å¿ƒç†çŠ¶æ€åŠå ¶å½±å“å› ç´ .

OBJECTIVES: To understand the psychological status of the staff in a general hospital during the coronavirus disease 2019 and its influential factors, and to provide references for the mental health services to hospital staff. METHODS: Using star platform of questionnaire, the staff in the general hospital were investigated via Depression, Anxiety, Stress Scale (DASS-21), Social Support Rating Scale (SSRS) and Simplified Coping Style Questionnaire (SCSQ). The influential factors were discussed by descriptive analysis, rank sum test, single factor analysis, correlation analysis and multiple factors binary logistic regression analysis. RESULTS: A total of 2 060 valid questionnaires were collected. The negative emotions of nurses and cleaners were the most obvious. The depression scores, anxiety scores and stress scores for nurses and cleaners were 5.06±7.47, 6.36±7.84, 9.75±8.65, and 6.72±8.84, 4.51±6.56, 9.69±9.56, respectively. Multivariate binary logistic regression analysis showed that staff types, education levels, job status, economic situation and concerns on the supplies of protective goods were the main influential factors for depression; staff types, contacting status with infected patients, economic situation, concerns on the supplies of protective goods, history of disease were the main influential factors for anxiety; contacting status with infected patients, economic situation, concerns on the supplies of protective goods were the main influential factors for stress. CONCLUSIONS: There are differences in psychological characteristics among different groups of staff in the general hospital under the outbreak. Thus psychological protection and intervention measures should be formulated according to different groups and work status.

[Removal of BPA and EE2 from Water by Mn-Fe Embedded in Acicular Mullite].

Acicular mullite was modified by ferromanganese binary metal oxide (Mn-Fe) to improve the removal efficiency of endocrine disruptors by traditional water treatment practices, using the commercial ceramsite for comparison. The physicochemical properties of synthesized samples were characterized, and batch adsorption experiments were carried out to study the adsorption efficiency of bisphenol A (BPA) and 17α-ethinylestradiol (EE2) on synthesized samples, investigating how solution chemistry and regeneration may affect the adsorption efficiency. Results show that the manganese oxide loaded on the acicular mullite was manganite with an average particle size of 450 nm. After Mn-Fe impregnation, the specific surface area, cumulative pore volume, and mesoporous ratio of the acicular mullite were significantly increased. The virgin acicular mullite had no removal ability for BPA and EE2, and the removal efficiency of BPA and EE2 by Mn-Fe impregnated acicular mullite were significantly increased. Acicular mullite was more suitable as support material for modified filter material. The adsorption kinetics of BPA and EE2 on Mn-Fe-M were fitted with the intra-particle diffusion model, and found to be mainly affected by intra-particle diffusion. The isothermal adsorption data was best fitted to the Langmuir-Freundlich model, and the maximum adsorption capacities of BPA and EE2 were 5.043 mg·g-1 and 3.990 mg·g-1, respectively. Thermodynamic experiments showed that the adsorption of BPA and EE2 by Mn-Fe embedded in acicular mullite was an endothermic reaction, and the temperature increase is beneficial to the adsorption. The adsorption amount of BPA and EE2 on Mn-Fe embedded in acicular mullite decreased with increasing pH. The increase of ionic strength favored the adsorption removal of BPA and EE2. The co-existing anion of SO42- promoted the adsorption of both BPA and EE2, while CO32- and PO43- inhibited the adsorption of both BPA and EE2 on Mn-Fe embedded in acicular mullite. The adsorbent regeneration test showed that Mn-Fe embedded acicular mullite was an easily recyclable adsorbent. Mn-Fe embedded in high-porosity acicular mullite can effectively remove typical endocrine disruptors in water, and it can be potentially extensively used to alleviate the problem of low removal efficiency of endocrine disrupting chemicals in traditional water treatment practice.

Incredulity on assumptions for the simplified Bohart-Adams model: 17a-ethinylestradiol separation in lab-scale anthracite columns.

In this study, the original Bohart-Adams model was employed to analyze the experimental data of 17α-ethinylestradiol (EE2) separation in lab-scale anthracite columns with low initial concentration. Besides, the assumptions for the simplified Bohart-Adams model were calculated and discussed. The results revealed that the breakthrough curves of EE2 separation in anthracite columns under different conditions were asymmetrical N-shaped and could be divided into three parts. The third part of the breakthrough curves was successfully fitted by the original Bohart-Adams model with high R2 values (higher than 0.918) and low ARS values (less than 0.141). As expected, the assumptions for the simplified Bohart-Adams model were not tenable during the whole experiment process. As a result, the EE2 separation capacities (N0° and N0s) obtained from the original and simplified Bohart-Adams model were quite different, and most N0° values were greater than N0s values. The N0° value used to evaluate the pollutant separation capacity in lab-scale column would be more accurate. In addition, physical interception and chemical adsorption simultaneously worked in the EE2 separation in anthracite columns. Physical interception and bed depth in anthracite columns at low flow rate were related in quadratic function (R2 > 0.988).

[Clinical analysis for patients with diabetic foot among multiple centers in China].

OBJECTIVE: To explore the clinical characteristics, risk factors and factors affecting the severity of the disease in patients with diabetic foot at the current stage through a multi-center cross-sectional survey.
 Methods: Clinical data of 326 patients with diabetic foot (205 males and 121 females) from 13 general hospitals nationwide were collected from October to November 2017 using a unified clinical data collection table. The clinical characteristics were analyzed, and the influential factors for severe diabetic foot were analyzed by logistic regression analysis.
 Results: Among 326 patients with diabetic foot, 68.4% of the patients were more than 60 years old, and 60.1% of the patients received primary or junior high school education; 96.3% of the patients developed Type 2 diabetes; 80.1% of patients had glycated hemoglobin (HbA1c)≥7%; 60.1% of patients suffered dyslipidemia. Improper wearing of footwear (38.5%) is the main cause of diabetic foot. Diabetic neuropathy (76.7%), diabetic retinopathy (62.3%) and lower limb vascular disease (57.4%) were the most common complications. Logistic regression analysis showed that diabetic nephropathy, diabetic lower extremity vascular disease, and HbA1c levels were independent risk factors for severe diabetic foot, and receiving foot care education can be regarded as a protective factor.
 Conclusion: The diabetic foot occurs mostly in male patients, and Type 2 diabetes with older age, lower education level, poor glycemic control and dyslipidemia are the risk factors. Diabetic nephropathy, diabetic lower extremity vascular disease, HbA1c, and receiving foot care education are independent influential factors for the severity of diabetic foot.

Adsorption characteristics of nitrite on natural filter medium: Kinetic, equilibrium, and site energy distribution studies.

Nitrite is one of the world's major contaminants in drinking water resources, and granular anthracite is often used as filter medium in water treatment. In this study, the adsorption characteristics of nitrite on granular anthracite under various temperatures were investigated through adsorption kinetic, isotherm models, and site energy distribution theory. The adsorption of nitrite on granular anthracite was an endothermic reaction, while intraparticle diffusion was not the only rate control step. The adsorption could be well described by using pseudo-second-order and Langmuir-Freundlich equations. The adsorption capacity was 402.51 mg NO2--N kg-1 at 298 K, which could be significantly improved to 1380.1 mg NO2--N kg-1 when the temperature reached 308 K. Furthermore, nitrite ions first occupied the high-energy adsorption sites and then diffused to the low-energy adsorption sites on granular anthracite. There were more sites, including high-energy sites and low-energy sites, for nitrite adsorption at 308 K. Besides, the thickness of the boundary layer increased with the adsorption capacity improved at a higher temperature, and nitrite ions were adsorbed mainly through chemical mechanisms. Moreover, the neutral pH was helpful for the adsorption. The presence of co-existing ions could limit the adsorption and the effect followed the order of PO43- > CO32- > SO42- > NO3- > Cl-. The saturated anthracite could be effectively regenerated by 0.2 mol L-1 HCl solution. Therefore, the granular anthracite used as filter medium also has a possible application as a nitrite scavenger at the same time.

Analysis of 17α-ethinylestradiol and bisphenol A adsorption on anthracite surfaces by site energy distribution.

17α-Ethinylestradiol (EE2) and bisphenol A (BPA) are highly toxic and widely detected endocrine-disrupting compounds (EDCs) throughout the world in surface waters. Adsorption is an effective way to remove EE2 and BPA from water. However, it is difficult to clearly explain the mechanism of adsorption theoretically only through classic adsorption models. In order to insight into the adsorption of EE2 and BPA, site energy distribution (SED) theory was introduced to investigate the adsorption of EE2 and BPA on heterogeneous surfaces. EE2 and BPA were adsorbed on un-anthracite (unmodified anthracite) and 4K anthracite (4 mol L-1 KOH-modified anthracite) in single- and bi-component systems under various temperatures and pHs. The results suggested that EE2 and BPA molecules first occupied the high-energy adsorption sites and then spread to low-energy adsorption sites. There were more high-energy sites on 4K anthracite, resulting in a higher adsorption capability for EE2 and BPA. Besides, increasing temperature and acidic environment were conducive to the EE2 and BPA adsorption. SED analyses indicated that, in neutral solutions, π-π electron donor-acceptor (EDA) interaction might be the primary mechanism for BPA adsorption, while ligand exchange, hydrogen bonds, and π-π EDA interaction might simultaneously work in the adsorption of EE2. It was possible that EE2 molecule was near perpendicular to surface, while BPA molecule was parallel to surface, resulting in the higher adsorption capacities of EE2. However, compared with EE2, BPA had outstanding competitive advantages in bi-component system because of the stronger π-π EDA interaction between BPA and anthracite.