BACKGROUND: Diabetic foot is a complex condition with high incidence, recurrence, mortality, and disability rates. Current treatments for diabetic foot ulcers are often insufficient. This study was conducted to identify potential therapeutic targets for diabetic foot. METHODS: Datasets related to diabetic foot and diabetic skin were retrieved from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified using R software. Enrichment analysis was conducted to screen for critical gene functions and pathways. A protein interaction network was constructed to identify node genes corresponding to key proteins. The DEGs and node genes were overlapped to pinpoint target genes. Plasma and chronic ulcer samples from diabetic and non-diabetic individuals were collected. Western blotting, immunohistochemistry, and enzyme-linked immunosorbent assays were performed to verify the S100 calcium binding protein A9 (S100A9), inflammatory cytokine, and related pathway protein levels. Hematoxylin and eosin staining was used to measure epidermal layer thickness. RESULTS: In total, 283 common DEGs and 42 node genes in diabetic foot ulcers were identified. Forty-three genes were differentially expressed in the skin of diabetic and non-diabetic individuals. The overlapping of the most significant DEGs and node genes led to the identification of S100A9 as a target gene. The S100A9 level was significantly higher in diabetic than in non-diabetic plasma (178.40 ± 44.65 ng/mL vs. 40.84 ± 18.86 ng/mL) and in chronic ulcers, and the wound healing time correlated positively with the plasma S100A9 level. The levels of inflammatory cytokines (tumor necrosis factor-α, interleukin [IL]-1, and IL-6) and related pathway proteins (phospho-extracellular signal regulated kinase [ERK], phospho-p38, phospho-p65, and p-protein kinase B [Akt]) were also elevated. The epidermal layer was notably thinner in chronic diabetic ulcers than in non-diabetic skin (24.17 ± 25.60 μm vs. 412.00 ± 181.60 μm). CONCLUSIONS S100A9 was significantly upregulated in diabetic foot and was associated with prolonged wound healing. S100A9 may impair diabetic wound healing by disrupting local inflammatory responses and skin re-epithelialization.
Calgranulin B/therapeutic use* ; Diabetic Foot/metabolism* ; Humans ; Datasets as Topic ; Computational Biology ; Mice, Inbred C57BL ; Animals ; Mice ; Protein Interaction Maps ; Immunohistochemistry

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

Objective To systematically evaluate the effects of liraglutide combined with metformin on glucose and lipid metabolism,sex hormones,reproductive function,and gastrointestinal reactions in patients with polycystic ovary syndrome(PCOS).Methods We searched databases such as PubMed,WanFang Medical Network,WanFang Database,China National Knowledge Infrastructure(CNKI),and VIP Journals to collect randomized controlled trials published from January 2011 to August 2022 on the treatment of polycystic ovary syndrome with liraglutide combined with metformin,using Revman 5.4 for the meta-analysis.Results A total of 16 case-control studies were included,involving 1436 patients.Compared to metformin alone,the combination of liraglutide and metformin significantly lowered fasting blood sugar,postprandial blood glucoseafter 2 hours,HbA1c,HOMA-IR,FINS,BMI,as well as LH,FSH,and total testosterone in patients with PCOS.It improved lipid levels,helped establish menstrual cycles,and increased the normal ovulation rate and natural conception rate in these patients.However,there was a significantly higher incidence of gastrointestinal reactions in the liraglutide plus metformin group,and the difference was statistically significant(P＜0.05).Conclusion The combination of liraglutide and metformin can improve glucose and lipid metabolism in patients with polycystic ovary syndrome(PC OS),reduce levels of LH,FSH,and total testosterone,help establish regular menstrual cycles,and increase ovulation and pregnancy rates,but it significantly increases gastrointestinal side effects.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Purpose To evaluate the effectiveness of deep learning image reconstruction(DLIR)algorithms in reconstructing lumbar vertebrae images from abdominal CT scans,aiming to reduce radiation dose and eliminate the need for repeat lumbar CT examinations.Materials and Methods A retrospective collection was conducted from March to May 2024 in the First Affiliated Hospital of Tianjin University of Traditional Chinese Medicine.Thirty-two patients who underwent both abdominal and lumbar CT scans in a supine head-first position were enrolled.The abdominal CT(DLIR group)utilized a tube voltage of 120 kVp and a current of 200 mA with high-intensity DLIR for lumbar reconstruction.The standard lumbar CT(lumbar group)used the same voltage with a tube current of 260 mA and was reconstructed using 60%weighted adaptive statistical iterative reconstruction.Objective assessments was used to measure the CT values,noise(standard deviation,SD value),signal-to-noise ratio and contrast-to-noise ratio(excluding adipose tissue)at the third lumbar vertebral pedicle level and the L2/L3 intervertebral disc level for muscle,adipose tissue,cancellous bone,intervertebral discs,dura mater and cortical bone.Subjective assessments employed a five-point scale to evaluate image contrast,noise and sharpness.Results The volume CT dose index in lumbar group and DLIR group were 15.25 mGy and 11.74 mGy,respectively.There was no statistical difference in CT values between the structures of both groups(all P>0.05).Compared with the lumbar group,the DLIR group showed significant reductions in SD values across the measured tissues by 31.09%,35.66%,13.48%,27.82%,24.93%and 15.09%(t=5.09-7.21,all P<0.05).The signal-to-noise ratio improved by 36.40%,52.31%,16.56%,34.13%,38.39%and 18.81%,and the contrast-to-noise ratio improved by 51.70%,51.32%,36.24%,34.47%and 53.56%(t=-9.58--4.23,all P<0.001).The DLIR group significantly outperformed the lumbar group in image contrast[4.45(4.00,5.00)points vs.4.75(4.00,5.00)points],image noise[4.06(4.00,4.00)points vs.4.39(4.00,5.00)points],and spatial resolution of fine structures[4.00(4.00,4.00)points vs.4.27(4.00,5.00)points](Z=-3.80,-4.38,-3.55,all P<0.001).Conclusion Using high-intensity DLIR for abdominal examinations can achieve high-quality lumbar CT images with a 25%reduction in radiation dose,enabling simultaneous abdominal and lumbar scanning in a single session.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Purpose To evaluate the effectiveness of deep learning image reconstruction(DLIR)algorithms in reconstructing lumbar vertebrae images from abdominal CT scans,aiming to reduce radiation dose and eliminate the need for repeat lumbar CT examinations.Materials and Methods A retrospective collection was conducted from March to May 2024 in the First Affiliated Hospital of Tianjin University of Traditional Chinese Medicine.Thirty-two patients who underwent both abdominal and lumbar CT scans in a supine head-first position were enrolled.The abdominal CT(DLIR group)utilized a tube voltage of 120 kVp and a current of 200 mA with high-intensity DLIR for lumbar reconstruction.The standard lumbar CT(lumbar group)used the same voltage with a tube current of 260 mA and was reconstructed using 60%weighted adaptive statistical iterative reconstruction.Objective assessments was used to measure the CT values,noise(standard deviation,SD value),signal-to-noise ratio and contrast-to-noise ratio(excluding adipose tissue)at the third lumbar vertebral pedicle level and the L2/L3 intervertebral disc level for muscle,adipose tissue,cancellous bone,intervertebral discs,dura mater and cortical bone.Subjective assessments employed a five-point scale to evaluate image contrast,noise and sharpness.Results The volume CT dose index in lumbar group and DLIR group were 15.25 mGy and 11.74 mGy,respectively.There was no statistical difference in CT values between the structures of both groups(all P>0.05).Compared with the lumbar group,the DLIR group showed significant reductions in SD values across the measured tissues by 31.09%,35.66%,13.48%,27.82%,24.93%and 15.09%(t=5.09-7.21,all P<0.05).The signal-to-noise ratio improved by 36.40%,52.31%,16.56%,34.13%,38.39%and 18.81%,and the contrast-to-noise ratio improved by 51.70%,51.32%,36.24%,34.47%and 53.56%(t=-9.58--4.23,all P<0.001).The DLIR group significantly outperformed the lumbar group in image contrast[4.45(4.00,5.00)points vs.4.75(4.00,5.00)points],image noise[4.06(4.00,4.00)points vs.4.39(4.00,5.00)points],and spatial resolution of fine structures[4.00(4.00,4.00)points vs.4.27(4.00,5.00)points](Z=-3.80,-4.38,-3.55,all P<0.001).Conclusion Using high-intensity DLIR for abdominal examinations can achieve high-quality lumbar CT images with a 25%reduction in radiation dose,enabling simultaneous abdominal and lumbar scanning in a single session.

AIM: To analyze the distribution frequency of gene polymorphisms of β receptor blockers, angiotensin receptor antagonists, angiotensin converting enzyme inhibitors, calcium antagonists, and diuretics in hypertensive patients from southern Anhui province, and provide a theoretical basis for gene detection of hypertension drugs and personalized medication. METHODS: Drug gene testing information from 839 hospitalized patients with hypertension at Yijishan Hospital of Wannan Medical College from July 2021 to April 2023 were collected, and the distribution frequency of each gene locus were analyzed. RESULTS: The genotype frequencies of ACE (I/D) I/I, I/D, and D/D were 42.1%, 46.0%, and 11.9%, respectively. the genotype frequencies of ADRB1 (1165G>C) G/G, G/C, and C/C were 8.3%, 40.0%, and 51.6%, respectively. The genotype frequencies of AGTR1 (1166A>C) A/A, A/C, and C/C were 90.2%, 9.8%, and 0.0%. The genotype frequencies of CYP2C9*3 (1075A>C) *1/*1, *1/*3, and *3/*3 were 91.3%, 8.7%, and 0.0%, respectively; the genotype frequencies of CYP2D6* 10 (100C > T) *1/*1, *1/*10, and *10/*10 were 25.0%, 36.6%, and 38.4%, respectively. The genotype frequencies of CYP3A5*3 (6986A>G) *1/*1, *1/*3, and *3/*3 were 7.0%, 39.0%, and 54.0%, respectively. The frequencies of NPPA (2238T>C) T/T, T / C, and C / C genotypes were 97.9%, 2.1%, and 0.0%, respectively. In addition, there was a significant difference in the genotype distribution frequency of multiple drug related gene loci in southern Anhui compared to other regions in China (P< 0.05). CONCLUSION: The genotype distribution frequency of hypertensive drug related gene loci had certain bias in southern Anhui, and were significant different from other regions in China, indicating that conducting genetic polymorphism testing of hypertensive drugs had certain guiding significance for the individualized application of hypertensive drugs in southern Anhui.

OBJECTIVE: To observe the clinical effect of electroacupuncture at acupoints of yangming meridians for sarcopenia. METHODS: A total of 60 patients with sarcopenia were randomized into an observation group and a control group, 30 cases in each group. In the control group, conventional nutrition intervention for sarcopenia was adopted. In the observation group, on the basis of the treatment in the control group, acupuncture was applied at bilateral Binao (LI 14), Quchi (LI 11), Zusanli (ST 36), Yanglingquan (GB 34), etc.,ipsilateral Quchi (LI 11) and Zusanli (ST 36) were connected to electroacupuncture, with discontinuous wave, 2 Hz in frequency, 1-10 mA in intensity, 2 times a week, with a interval of 3 days. A total of 12-week treatment was required in the two groups. Before and after treatment, the appendicular skeletal muscle mass index (ASMI), grip strength, 6 m-walking time, body fat percentage and body moisture percentage were observed in the two groups. RESULTS: Compared with those before treatment, after treatment, ASMI and grip strength were increased while 6 m-walking time was shortened in the two groups (P<0.05); body fat percentage was decreased while body moisture percentage was increased in the observation group (P<0.05). After treatment, in the observation group, ASMI, grip strength and body moisture percentage were increased (P<0.05), 6 m-walking time was shortened and body fat percentage was decreased (P<0.05) compared with those in the control group. CONCLUSION Electroacupuncture at acupoints of yangming meridians can effectively improve the skeletal muscle mass, muscle function, body fat percentage and body moisture percentage in patients with sarcopenia, and make the distribution of muscle and fat more reasonable.
Humans ; Meridians ; Acupuncture Points ; Electroacupuncture ; Sarcopenia/therapy* ; Acupuncture Therapy

Objectives To analyze the risk factors and their predictive value for postoperative hypoxemia in Type-A aortic dissection(TAAD).Methods A single-center retrospective study was conducted among 146 consecutive patients diagnosed as TAAD and undergone aortic arch surgery from January 2018 to June 2021 in Nanfang Hospital of Southern Medical University.According to the lowest postoperative PaO2/FiO2 ratio within 24 hours,the patients were classified into two groups:hypoxemia group(PaO2/FiO2≤200 mmHg)and non-hypoxemia group(PaO2/FiO2>200 mmHg).The difference of preoperative oxygen index,duration of mechanical ventilation and mortality in hospital were analyzed between the two groups.The independent risk factors for postoperative hypoxemia were evaluated by multivariate logistic regression and the predictive value was analyzed by receiver operator character(ROC)curves.Results For TAAD patients,the incidence of postoperative hypoxemia was 45.9%.Compared to non-hypoxemia group,hypoxemia group exhibited longer duration of mechanical ventilation(P<0.001)and longer intensive care unit(ICU)length of stay(P<0.05).Moreover,patients with hypoxemia presented higher mortality during hospital(P=0.011).Multivariate regression analysis identified BMI as independent risk factor(OR=1.701,P<0.001)and preoperation PaO2/FiO2 ratio as protective factors for postoperative hypoxemia in patients with TAAD(OR=0.987,P=0.004).Area under the ROC curve of BMI was 0.848,the optimal cut-off point of BMI was 25.8 kg/m2.Area under the ROC curve of pre-operation PaO2/FiO2 ratio was 0.808,the optimal cut-off point of preoperation PaO2/FiO2 ratio was 265 mmHg.Conclusions BMI higher than 25.8 kg/m2 is an independent risk factor and preoperation PaO2/FiO2 ratio higher than 265 mmHg is a protective factor for postoperative hypoxemia in patients with TAAD.Subjects with hypoxemia had longer duration of mechanical ventilation,ICU stay and higher mortality.