Predicting protein-coding genes still remains a significant challenge. Although a variety of computational programs that use commonly machine learning methods have emerged, the accuracy of predictions remains a low level when implementing in large genomic sequences. Moreover, computational gene finding in newly sequenced genomes is especially a difficult task due to the absence of a training set of abundant validated genes. Here we present a new gene-finding program, SCGPred,to improve the accuracy of prediction by combining multiple sources of evidence.SCGPred can perform both supervised method in previously well-studied genomes and unsupervised one in novel genomes. By testing with datasets composed of large DNA sequences from human and a novel genome of Ustilago maydi, SCGPred gains a significant improvement in comparison to the popular ab initio gene predictors. We also demonstrate that SCGPred can significantly improve prediction in novel genomes by combining several foreign gene finders with similarity alignments, which is superior to other unsupervised methods. Therefore, SCGPred can serve as an alternative gene-finding tool for newly sequenced eukaryotic genomes. The program is freely available at http://bio.scu.edu.cn/SCGPred/.

Objective:To explore the efficacy of sheet hydrogel dressings in the prevention of acute radiodermatitis.Methods:A total of 120 patients,who underwent the first radiotherapy were randomly divided into the control group and the study group, with 60 cases in each group.The control group was treated by external application with Lifuning(skin protection agent for radiation therapy)and the study group was treated by external application with sheet hydrogel dressings.The occurrence time and the grade of acute radiodermatitis at the first onset were compared between the two groups.Results:The occurrence time of acute radiodermatitis was significantly later in the study group than that in the control group(P <0.01).The grade of acute ra-diodermatitis at the first onset was significantly lower in the study group than that in the control group(P <0.01).Conclusions:Sheet hydrogel dressings can prevent the occurrence of acute radiodermatitis effectively.

Objective:To observe the clinical efficacy of adhesive hydrocellular foam dressing for the treatment of radiodermati‐tis in patients with breast cancer after radiotherapy .Methods:A total of 50 patients with breast cancer who received radiothera‐py from Jan 2012 to Sep 2014 were recruited in the study group ,and adhesive hydrocellular foam dressing were applied to treat radiodermatitis .And 50 patients with breast cancer from Feb 2009 to Oct 2011 who received vitamin B12 by topical application were recruited as control group .The two groups were compared in frequency of dressing change ,healing time ,degree of pain , cost and interference on radiotherapy .Results:There were significant differences between study group and control group in fre‐quency of dressing change ,healing time ,degree of pain ,cost and interference on radiotherapy(P<0 .05) .Conclusions:Adhesive hydrocellular foam dressing has significant advantage in treating radiodermatitis resulting from radiotherapy in patients with breast cancer .

Predicting protein-coding genes still remains a significant challenge. Although a variety of computational programs that use commonly machine learning methods have emerged, the accuracy of predictions remains a low level when implementing in large genomic sequences. Moreover, computational gene finding in newly sequenced genomes is especially a difficult task due to the absence of a training set of abundant validated genes. Here we present a new gene-finding program, SCGPred, to improve the accuracy of prediction by combining multiple sources of evidence. SCGPred can perform both supervised method in previously well-studied genomes and unsupervised one in novel genomes. By testing with datasets composed of large DNA sequences from human and a novel genome of Ustilago maydi, SCG-Pred gains a significant improvement in comparison to the popular ab initio gene predictors. We also demonstrate that SCGPred can significantly improve prediction in novel genomes by combining several foreign gene finders with similarity alignments, which is superior to other unsupervised methods. Therefore, SCG-Pred can serve as an alternative gene-finding tool for newly sequenced eukaryotic genomes. The program is freely available at http://bio.scu.edu.cn/SCGPred/.
Algorithms ; Chromosome Mapping ; methods ; Computational Biology ; methods ; Exons ; genetics ; Genes, Fungal ; genetics ; Genome, Fungal ; Genome, Human ; Humans ; Reproducibility of Results ; Software ; Ustilago ; genetics

Objective:To explore the team construction and treatment strategy of the Diabetic Foot-Multidisciplinary Team.Methods:The clinical data of 19 patients with severe ischemic diabetic foot treated by our Diabetic Foot-Multidisciplinary Team Center from Apr 2021 to Mar 2022 were collected, and the overall amputation rate, above-ankle major amputation rate, minor amputation rate and mortality, Diabetic Foot-Multidisciplinary Team consultation discipline participation rate and treatment participation degree were retrospectively analyzed.Results:Nineteen patients (15 males and 4 females) were enrolled, aged 26 to 94 (68.6±14.2). All were with severe ischemic diabetic foot ulcer:Rutherford grade 5 or up and dysfunction in 2 or more organs. Complications included arteriosclerosis obliterans of the lower extremities in 18 cases, heart diseases in 18, hypertension in 15, and renal insufficiencies in 10. The overall amputation rate was 36.8%, major amputation rate in 21.1%, minor amputation rate in 15.8%, and mortality rate was 15.8%. A total of 16 disciplines participated in Diabetic Foot-Multidisciplinary Team; the main participating disciplines were vascular surgery (19 times), endocrinology (12 times), and cardiology (11 times). The main treatment disciplines were vascular surgery (14 times), plastic surgery (3 times), and cardiology (2 times).Conclusion:For the diagnosis and treatment of diabetic foot, it is necessary to set up a multidisciplinary team as early as possible to control the causes of diabetic foot ulcer, prevent the recurrence of diabetic foot ulcer, reduce the mortality and amputation rate, and improve the quality of life of patients.

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.
China ; Cross-Sectional Studies ; Diabetes Mellitus, Type 2 ; Diabetic Foot ; Diabetic Neuropathies ; Female ; Humans ; Male ; Middle Aged

Statistics show that 76.74% (4 688) of 6 109 patients with chronic wounds are those over 50 years of age; the proportion of patients with underlying diseases in all age groups above 50 years ranges from 78.25% to 100.00%; among the underlying diseases of chronic wound patients, the top four diseases are diabetes mellitus , cardiovascular and cerebrovascular diseases, hypertension, and respiratory diseases. The above underlying diseases and ages of patients are the susceptibility factors of corona virus disease 2019 released by National Health Commission of China. It is an unavoidable fact that patients with chronic wounds have to go to the hospital for treatment prescribed by the physician. At the same time, we found that there were not a few patients who go far afield because of various reasons when go to the hospital for treatment. During the period of epidemic prevention and control, this kind of "go far afield" style of seeking medical treatment may increase the exposure risk during transportation. Accordingly, we convened 36 wound care clinics in different regions in Shanghai to implement the "Five Measures" to encourage patients with chronic wounds to seek medical treatment proximately. The principle of this operation is that when seeking medical treatment, trying our best to reduce as much as possible the transportation distance for patients with chronic wounds to minimize the exposure risk during the epidemic period and eventually support the epidemic prevention and control campaign.