BACKGROUND:Synthetic polymers,such as polypropylene and polyester,used for the treatment of abdominal wall defects not only lack biodegradability and bioactivity but also fail to meet the demands of complex and irregular wounds.Therefore,finding bioactive materials with low immunogenicity and good histocompatibility has become a hot spot in the repair of abdominal wall defects. OBJECTIVE:To prepare methacryloyl modified dermal extracellular matrix hydrogel and explore its potential application in abdominal wall defect. METHODS:(1)The porcine dermis was acellular with 0.25%trypsin and 1%Triton X-100 in turn to obtain the dermal extracellular matrix.After pepsin digestion and methacrylic anhydride modification,the methacrylated dermal extracellular matrix hydrogel was formed by photocrosslinking.The microscopic morphology of the hydrogel was observed by scanning electron microscope,and its rheological properties,swelling properties and other physical and chemical properties were tested.(2)Mice fibroblasts(L929)were inoculated into methacrylated dermal extracellular matrix hydrogel to detect the cell compatibility.(3)Totally 12 SD rats were randomly divided into two groups(n=6)to create abdominal wall defect model with peritoneum preserved.The defect site of the polypropylene group was filled with polypropylene material,and the hydrogel group was filled with methacrylated dermal extracellular matrix hydrogel.The wound skin of both groups was covered with polypropylene material.The wound healing was observed and histological analysis was carried out. RESULTS AND CONCLUSION:(1)Enzymatic hydrolysis had a good decellularization effect on porcine dermis after decellularization,and the original glycosaminoglycans and collagen were well retained.Scanning electron microscope observation revealed that the dermal extracellular matrix hydrogel presented loose and porous structure.The aperture was between 70 and 120 μm.The swelling ratio was(16.88±3.24)%and the water absorption was(94.24±1.11)%.The rheological property test showed that the methacrylated dermal extracellular matrix hydrogel was stable and had shear thinning characteristics,with injectability.(2)CCK-8 assay and live/dead staining showed that methacrylated dermal extracellular matrix hydrogel had good cell compatibility.(3)The results of animal experiments showed that the skin wound healing rate of the experimental group was higher than that of the control group at 7,10,and 14 days after operation(P<0.05).Hematoxylin-eosin and Masson staining of skin and muscle tissue exhibited that compared with the polypropylene group,the skin wound epithelialization,hair follicle formation,collagen fiber arrangement,and neovascularization were better in the hydrogel group 14 days after surgery.The skin wound new tissue structure was similar to the normal tissue at 28 days after surgery,and scar hyperplasia was less.A small amount of muscle regeneration was observed on day 28 after operation.(4)The results show that the methacrylated dermal extracellular matrix hydrogel can promote wound skin healing and muscle tissue regeneration in rats with abdominal wall defect.

Study on the mechanism of Fangxia Dihuang Formula(FXDH) in treating breast cancer complicated with depression through the regulation of M1/M2 microglial polarization via the PERK/eIF2α axis. In addition to control group and 4T1 group, a mouse model of breast cancer complicated with depression was established using 4T1 cells combined with corticosterone. The mice were divided into model group, PERK/eIF2α signaling axis agonist(CCT020312, 2 mg·kg~(-1)·d~(-1)) group, CCT020312(2 mg·kg~(-1)·d~(-1)) + FXDH(13.65 g·kg~(-1)·d~(-1)) group, FXDH(13.65 g·kg~(-1)·d~(-1)) group, FXDH(13.65 g·kg~(-1)·d~(-1)) + Capecitabine Tablets(CAP, 390 mg·kg~(-1)·d~(-1)) group, and Fluoxetine Hydrochloride Capsules(FXT, 2.6 mg·kg~(-1)·d~(-1)) + CAP(390 mg·kg~(-1)·d~(-1)) group, with continuous intervention for 21 d. Depression-like behaviors in mice were assessed through sugar preference test and open field test. Hematoxylin-eosin(HE) staining was used to evaluate the morphology of tumor and hippocampal DG region neurons. Nissl staining was employed to detect changes in Nissl bodies in the hippocampal CA3 region. Immunofluorescence was used to observe cluster of differentiation 86(CD86)/ionized calcium-binding adapter molecule 1(Iba-1) and cluster of differentiation 206(CD206)/Iba-1 in hippocampal tissue. Real-time fluorescence quantitative polymerase chain reaction(RT-qPCR) was used to detect the mRNA expression of M1-type microglia [interleukin-6(IL-6), tumor necrosis factor-α(TNF-α)] and M2-type [arginase-1(Arg-1), IL-10] in hippocampal tissue. Western blot was used to detect the protein expression of key factors in the PERK/eIF2α axis, including PERK, eIF2α, activating transcription factor 4(ATF4), and C/EBP homologous protein(CHOP) in hippocampal tissue. The results showed that compared to model group/CCT020312 + FXDH group, FXDH group increased sugar preference index, total movement distance, central zone distance, and central zone entries; reduced tumor mass and volume; tumor cells were sparsely arranged, with a smaller nuclear-to-cytoplasmic ratio and reduced nuclear division figures, increased Nissl body count, and alleviated neuronal nuclear pyknosis; increased CD206-positive M2-type microglia expression, decreased CD86/Iba-1-positive M1-type microglia expression; reduced IL-6 and TNF-α mRNA expression, and increased Arg-1 and IL-10 mRNA expression; downregulated PERK, eIF2α, ATF4, and CHOP protein expression levels. The results indicate that the mechanism of FXDH in treating breast cancer complicated with depression may be related to inhibiting the activity of the PERK/eIF2α axis, reducing the proportion of M1-type microglia, increasing the proportion of M2-type microglia, thereby suppressing neuronal immune inflammation, improving depressive symptoms, and subsequently delaying the progression of breast cancer.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Female ; Microglia/cytology* ; Mice ; Depression/complications* ; eIF-2 Kinase/genetics* ; Humans ; Breast Neoplasms/psychology* ; Eukaryotic Initiation Factor-2/genetics* ; Mice, Inbred BALB C ; Signal Transduction/drug effects* ; Cell Line, Tumor

AIM: To assess the consistency of the new anterior segment analyzer, MS-39, the Sirius and Pentacam in measuring corneal white-to-white(WTW)and central anterior chamber depth(ACD), and to compare their differences in guiding implantable collamer lens(ICL)size selection.METHODS: Retrospective case study. A total of 210 consecutive patients(420 eyes)who treated at the Ophthalmology Refractive Surgery Center of the First Affiliated Hospital of Xi'an Jiaotong University between September 2019 and September 2020 were enrolled. Three anterior segment analysis systems, MS-39, Sirius, and Pentacam, were utilized to assess the WTW and ACD, with comparative analysis of the results. The sizing of the ICL V4c was simulated using the method recommended by the STAAR company. Data correlation and consistency were evaluated.RESULTS: The WTW measurement results obtained from MS-39, Sirius, and Pentacam were 11.39±0.35, 11.42±0.36, and 11.46±0.35 mm, respectively. Notably, the WTW measurement value from MS-39 was significantly lower than that from Pentacam(P=0.002), while no statistically significant differences were observed between MS-39 and Sirius, or between Sirius and Pentacam(all P>0.05). The WTW measurements from the three devices exhibited a strong positive correlation, with correlation coefficients(r)of 0.942 between MS-39 and Sirius, 0.925 between MS-39 and Pentacam, and 0.882 between Sirius and Pentacam(all P<0.0001). The ACD measurements values from the MS-39, Sirius and Pentacam were 3.28±0.22, 3.28±0.24, and 3.21±0.23 mm, respectively. While, no statistically significant difference was found between MS-39 and Sirius(P>0.05), both measurements were significantly higher than that of Pentacam(both P<0.0001). The ACD measurements also demonstrated a strong positive correlation, with r values of 0.959 between MS-39 and Sirius, 0.947 between MS-39 and Pentacam, and 0.932 between Sirius and Pentacam(all P<0.0001). In terms of ICL size selection based on the measurements from the three devices, the 12.6 mm size was the most frequently selected, while the 13.7 mm size was the least common, the distribution of size selections across the devices was similar.CONCLUSION: MS-39 demonstrated strong positive correlation with both Sirius and Pentacam for WTW and ACD measurements, indicating that the results can be considered clinically interchangeable. Furthermore, the outcomes derived from MS-39 for ICL size selection were closely aligned with those from Sirius and Pentacam, suggesting its clinical feasibility.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: The aim of this study was to investigate the feasibility of an intelligent handheld ultrasound (US) device for assisting non-expert general practitioners (GPs) in detecting carotid plaques (CPs) in community populations. Methods: This prospective parallel controlled trial recruited 111 consecutive community residents. All of them underwent examinations by non-expert GPs and specialist doctors using handheld US devices (setting A, setting B, and setting C). The results of setting C with specialist doctors were considered the gold standard. Carotid intima-media thickness (CIMT) and the features of CPs were measured and recorded. The diagnostic performance of GPs in distinguishing CPs was evaluated using a receiver operating characteristic curve. Inter-observer agreement was compared using the intragroup correlation coefficient (ICC). Questionnaires were completed to evaluate clinical benefits. Results: Among the 111 community residents, 80, 96, and 112 CPs were detected in settings A, B, and C, respectively. Setting B exhibited better diagnostic performance than setting A for detecting CPs (area under the curve, 0.856 vs. 0.749; P<0.01). Setting B had better consistency with setting C than setting A in CIMT measurement and the assessment of CPs (ICC, 0.731 to 0.923). Moreover, measurements in setting B required less time than the other two settings (44.59 seconds vs. 108.87 seconds vs. 126.13 seconds, both P<0.01). Conclusion Using an intelligent handheld US device, GPs can perform CP screening and achieve a diagnostic capability comparable to that of specialist doctors.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: The aim of this study was to investigate the feasibility of an intelligent handheld ultrasound (US) device for assisting non-expert general practitioners (GPs) in detecting carotid plaques (CPs) in community populations. Methods: This prospective parallel controlled trial recruited 111 consecutive community residents. All of them underwent examinations by non-expert GPs and specialist doctors using handheld US devices (setting A, setting B, and setting C). The results of setting C with specialist doctors were considered the gold standard. Carotid intima-media thickness (CIMT) and the features of CPs were measured and recorded. The diagnostic performance of GPs in distinguishing CPs was evaluated using a receiver operating characteristic curve. Inter-observer agreement was compared using the intragroup correlation coefficient (ICC). Questionnaires were completed to evaluate clinical benefits. Results: Among the 111 community residents, 80, 96, and 112 CPs were detected in settings A, B, and C, respectively. Setting B exhibited better diagnostic performance than setting A for detecting CPs (area under the curve, 0.856 vs. 0.749; P<0.01). Setting B had better consistency with setting C than setting A in CIMT measurement and the assessment of CPs (ICC, 0.731 to 0.923). Moreover, measurements in setting B required less time than the other two settings (44.59 seconds vs. 108.87 seconds vs. 126.13 seconds, both P<0.01). Conclusion Using an intelligent handheld US device, GPs can perform CP screening and achieve a diagnostic capability comparable to that of specialist doctors.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: The aim of this study was to investigate the feasibility of an intelligent handheld ultrasound (US) device for assisting non-expert general practitioners (GPs) in detecting carotid plaques (CPs) in community populations. Methods: This prospective parallel controlled trial recruited 111 consecutive community residents. All of them underwent examinations by non-expert GPs and specialist doctors using handheld US devices (setting A, setting B, and setting C). The results of setting C with specialist doctors were considered the gold standard. Carotid intima-media thickness (CIMT) and the features of CPs were measured and recorded. The diagnostic performance of GPs in distinguishing CPs was evaluated using a receiver operating characteristic curve. Inter-observer agreement was compared using the intragroup correlation coefficient (ICC). Questionnaires were completed to evaluate clinical benefits. Results: Among the 111 community residents, 80, 96, and 112 CPs were detected in settings A, B, and C, respectively. Setting B exhibited better diagnostic performance than setting A for detecting CPs (area under the curve, 0.856 vs. 0.749; P<0.01). Setting B had better consistency with setting C than setting A in CIMT measurement and the assessment of CPs (ICC, 0.731 to 0.923). Moreover, measurements in setting B required less time than the other two settings (44.59 seconds vs. 108.87 seconds vs. 126.13 seconds, both P<0.01). Conclusion Using an intelligent handheld US device, GPs can perform CP screening and achieve a diagnostic capability comparable to that of specialist doctors.