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Glaucoma infection is rapidly spreading globally and the number of glaucoma patients is expected to exceed 110 million by 2040. Early identification and detection of glaucoma is particularly important as it can easily lead to irreversible vision damage or even blindness if not treated with intervention in the early stages. Deep learning has attracted much attention in the field of computer vision and has been widely studied especially in the recognition and diagnosis of ophthalmic diseases. It is challenging to efficiently extract effective features for accurate grading of glaucoma in a limited dataset. Currently, in glaucoma recognition algorithms, 2D fundus images are mainly used to automatically identify the disease or not, but do not distinguish between early or late stages; however, in clinical practice, the treatment of early and late glaucoma is not the same, so it is more important to proceed to achieve accurate grading of glaucoma. This study uses a private dataset containing modal data, 2D fundus images, and 3D-OCT scanner images, to extract the effective features therein to achieve an accurate triple classification (normal, early, and moderately advanced) for optimal performance on various measures. In view of this, this paper proposes an automatic glaucoma classification method based on the attention mechanism and EfficientNetB3 network. The EfficientNetB3 network and ResNet34 network are built to extract and fuse 2D fundus images and 3D-OCT scanner images, respectively, to achieve accurate classification. The proposed auto-classification method minimizes feature redundancy while improving classification accuracy, and incorporates an attention mechanism in the two-branch model, which enables the convolutional neural network to focus its attention on the main features of the eye and discard the meaningless black background region in the image to improve the performance of the model. The auto-classification method combined with the cross-entropy function achieves the highest accuracy up to 97.83%. Since the proposed automatic grading method is effective and ensures reliable decision-making for glaucoma screening, it can be used as a second opinion tool by doctors, which can greatly reduce missed diagnosis and misdiagnosis by doctors, and buy more time for patient's treatment.
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Algoritmos , Aprendizaje Profundo , Glaucoma , Humanos , Glaucoma/diagnóstico , Glaucoma/diagnóstico por imagen , Redes Neurales de la Computación , Tomografía de Coherencia Óptica/métodosRESUMEN
OBJECTIVE: This study aimed to examine the correlation between preoperative body mass index (BMI) and adequate percentage of total weight loss (TWL%) outcome and present evidence of tiered treatment for patients with obesity in different preoperative BMI. METHODS: We included patients with complete follow-up data who underwent metabolic and bariatric surgery (BMS). We termed optimal clinical response as TWL% >20% at one year following MBS. To investigate dose-response association between preoperative BMI and optimal clinical response, preoperative BMI was analyzed in three ways: (1) as quartiles; (2) per 2.5 kg/m2 units (3) using RCS, with 3 knots as recommended. RESULTS: A total of 291 patients with obesity were included in our study. The corresponding quartile odds ratios associated with optimal clinical response and adjusted for potential confounders were 1.00 (reference), 1.434 [95% confidence interval (95%CI) = 0.589-3.495], 4.926 (95%CI = 1.538-15.772), and 2.084 (95%CI = 0.941-1.005), respectively. RCS analysis showed a non-linear inverted U-shaped association between preoperative BMI and optimal clinical response (Nonlinear P = 0.009). In spline analysis, when preoperative BMI was no less than 42.9 kg/m2, the possibility of optimal clinical response raised as preoperative BMI increased. When preoperative BMI was greater than 42.9 kg/m2, the possibility of optimal clinical response had a tendency to decline as preoperative BMI increased. CONCLUSION: Our research indicated the non-linear inverted U-shaped correlation between preoperative BMI and adequate weight loss. Setting a preoperative BMI threshold of 42.9 is critical to predicting optimal clinical outcomes.
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Cirugía Bariátrica , Índice de Masa Corporal , Pérdida de Peso , Humanos , Cirugía Bariátrica/métodos , Estudios Retrospectivos , Femenino , Masculino , Pérdida de Peso/fisiología , Persona de Mediana Edad , Adulto , Resultado del Tratamiento , Obesidad/complicaciones , Obesidad/cirugía , Obesidad Mórbida/cirugía , Obesidad Mórbida/complicacionesRESUMEN
Background: Some research have indicated that Bariatric and metabolic surgery (BMS) can reduce the risk of cardiovascular disease (CVD) among individuals with obesity. However, there are few reports available that focuses on assessing effect of BMS on the risk of CVD in Chinese population using multiple models. Objective: This research aims to assess the function of BMS on the risk of CVD in Chinese patients with obesity using multiple CVD risk models. Methods: We performed a retrospective analysis of the basic data and glycolipid metabolism data preoperatively and postoperatively from patients with obesity at our hospital. Subgroup analysis was carried out according to different surgical procedures. Then, the function of BMS on the risk of CVD in the Chinese population was assessed using four models, including: China-PAR risk model, Framingham risk score (FRS), World Health Organization (WHO) risk model, and Globorisk model. Results: We enrolled 64 patients, 24 (37.5%) of whom underwent laparoscopic sleeve gastrectomy (LSG) while 40 (62.5%) underwent Roux-en-Y gastric bypass (RYGB). The 10-year CVD risk for patients calculated using the China-PAR risk model decreased from 6.3% preoperatively to 2.0% at 1 year postoperatively and was statistically significantly different. Similarly, the 10-year CVD risk of patients calculated using the FRS, WHO, Global risk model decreased significantly at 1 year postoperatively compared to preoperatively. When the FRS risk model was used to calculate the patients' 30-year postoperative CVD risk, there was a significant decrease at 1 year after surgery compared to the preoperative period. When employing various models to evaluate the 10-year CVD risk for LSG and RYGB, no statistically significant difference was found in the 1-year postoperative RRR between the procedures. Conclusion: The CVD risk after BMS was significantly reduced compared to preoperatively. In terms of improving cardiovascular risk, SG and RYGB appear to be equally effective.
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Depression, a pervasive global mental disorder, profoundly impacts daily lives. Despite numerous deep learning studies focused on depression detection through speech analysis, the shortage of annotated bulk samples hampers the development of effective models. In response to this challenge, our research introduces a transfer learning approach for detecting depression in speech, aiming to overcome constraints imposed by limited resources. In the context of feature representation, we obtain depression-related features by fine-tuning wav2vec 2.0. By integrating 1D-CNN and attention pooling structures, we generate advanced features at the segment level, thereby enhancing the model's capability to capture temporal relationships within audio frames. In the realm of prediction results, we integrate LSTM and self-attention mechanisms. This incorporation assigns greater weights to segments associated with depression, thereby augmenting the model's discernment of depression-related information. The experimental results indicate that our model has achieved impressive F1 scores, reaching 79% on the DAIC-WOZ dataset and 90.53% on the CMDC dataset. It outperforms recent baseline models in the field of speech-based depression detection. This provides a promising solution for effective depression detection in low-resource environments.
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Aprendizaje Profundo , Depresión , Habla , Humanos , Depresión/diagnóstico , Redes Neurales de la ComputaciónRESUMEN
The incorporation of mechanically interlocked structures into polymer backbones has been shown to confer remarkable functionalities to materials. In this work, a [c2]daisy chain unit based on dibenzo-24-crown-8 is covalently embedded into the backbone of a polymer network, resulting in a synthetic material possessing remarkable shape-memory properties under thermal control. By decoupling the molecular structure into three control groups, we demonstrate the essential role of the [c2]daisy chain crosslinks in driving the shape memory function. The mechanically interlocked topology is found to be an essential element for the increase of glass transition temperature and consequent gain of shape memory function. The supramolecular host-guest interactions within the [c2]daisy chain topology not only ensure robust mechanical strength and good network stability of the polymer, but also impart the shape memory polymer with remarkable shape recovery properties and fatigue resistance ability. The incorporation of the [c2]daisy chain unit as a building block has the potential to lay the groundwork for the development of a wide range of shape-memory polymer materials.
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The purpose of this study was to explore the differential expression of Pax3, Rad51 and VEGF-C in esophageal gastric junction adenocarcinoma and distal gastric adenocarcinoma and their relationship with cancer occurrence and development. 57 patients with gastric cancer were included and divided into esophageal gastric junction adenocarcinoma group (n=28) and distal gastric adenocarcinoma group (n=29). The positive expressions of Pax3, Rad51 and VEGF-C in the control group were lower than those in the esophageal gastric junction adenocarcinoma group and distal gastric adenocarcinoma group respectively (P<0.05). In esophageal gastric junction adenocarcinoma with low differentiation, positive expressions of Pax3, Rad51, and VEGF-C surpassed those in high/medium differentiation (P<0.05). Serosa-infiltrated cases exhibited higher Pax3 and Rad51 expressions compared to non-infiltrated cases (P<0.05). Rad51 and VEGF-C positivity were notably elevated in cases with lymph node metastasis compared to those without (P<0.05). Distal gastric adenocarcinoma displayed higher VEGF expression than middle/low differentiated adenocarcinomas. Rad51 expression was significantly higher in women than in men (P<0.05). The positive rates of Pax3, Rad51, and VEGF-C were markedly increased in esophageal gastric junction adenocarcinoma and distal gastric adenocarcinoma compared to normal gastric tissue, and these were associated with the degree of differentiation, depth of invasion, and lymph node metastasis in patients. Particularly, Rad51 exhibited a positive correlation with cancer cell differentiation, invasion depth, and lymph node metastasis in cancer tissue.
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Adenocarcinoma , Neoplasias Esofágicas , Factor de Transcripción PAX3 , Recombinasa Rad51 , Neoplasias Gástricas , Factor C de Crecimiento Endotelial Vascular , Femenino , Humanos , Masculino , Adenocarcinoma/genética , Adenocarcinoma/patología , Neoplasias Esofágicas/genética , Neoplasias Esofágicas/patología , Metástasis Linfática , Neoplasias Gástricas/genética , Neoplasias Gástricas/patología , Factores de Transcripción , Factor C de Crecimiento Endotelial Vascular/genética , Factor de Transcripción PAX3/genética , Recombinasa Rad51/genéticaRESUMEN
Lipoma is a common type of benign soft tissue tumor that can occur in the shoulders, neck and back, in addition to other body parts. The Retzius space is a small anatomical space between the pubic symphysis and the bladder located extraperitoneally and filled with loose fatty connective tissue. Giant lipomas are rare in the Retzius space. A 61-year-old Chinese male arrived at Beijing Yanhua Hospital (Beijing, China) due to frequent urination, and CT scan images of the lower abdomen observed a large pelvic mass and left inguinal hernia. Preoperative clinical manifestations and auxiliary examination suggested that the tumor originated from the urinary bladder wall. The maximum tumor diameter was ~25 cm and abdominal pressure was increased. Therefore, laparoscopic pelvic tumor resection combined with inguinal hernia repair was attempted. Intraoperatively, the tumor was found to originate from the Retzius space and the postoperative pathological diagnosis was lipoma. The present case report may serve as a reference for minimally invasive treatment of this type of rare disease in future.
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BACKGROUND: The effect of bariatric surgery on type 2 diabetes mellitus (T2DM) control can be assessed based on predictive models of T2DM remission. Various models have been externally verified internationally. However, long-term validated results after laparoscopic sleeve gastrectomy (LSG) surgery are lacking. The best model for the Chinese population is also unknown. METHODS: We retrospectively analyzed Chinese population data 5 years after LSG at Beijing Shijitan Hospital in China between March 2009 and December 2016. The independent t -test, Mann-Whitney U test, and chi-squared test were used to compare characteristics between T2DM remission and non-remission groups. We evaluated the predictive efficacy of each model for long-term T2DM remission after LSG by calculating the area under the curve (AUC), sensitivity, specificity, Youden index, positive predictive value (PPV), negative predictive value (NPV), and predicted-to-observed ratio, and performed calibration using Hosmer-Lemeshow test for 11 prediction models. RESULTS: We enrolled 108 patients, including 44 (40.7%) men, with a mean age of 35.5 years. The mean body mass index was 40.3 ± 9.1 kg/m 2 , the percentage of excess weight loss (%EWL) was (75.9 ± 30.4)%, and the percentage of total weight loss (%TWL) was (29.1± 10.6)%. The mean glycated hemoglobin A1c (HbA1c) level was (7.3 ± 1.8)% preoperatively and decreased to (5.9 ± 1.0)% 5 years after LSG. The 5-year postoperative complete and partial remission rates of T2DM were 50.9% [55/108] and 27.8% [30/108], respectively. Six models, i.e., "ABCD", individualized metabolic surgery (IMS), advanced-DiaRem, DiaBetter, Dixon et al' s regression model, and Panunzi et al 's regression model, showed a good discrimination ability (all AUC >0.8). The "ABCD" (sensitivity, 74%; specificity, 80%; AUC, 0.82 [95% confidence interval [CI]: 0.74-0.89]), IMS (sensitivity, 78%; specificity, 84%; AUC, 0.82 [95% CI: 0.73-0.89]), and Panunzi et al' s regression models (sensitivity, 78%; specificity, 91%; AUC, 0.86 [95% CI: 0.78-0.92]) showed good discernibility. In the Hosmer-Lemeshow goodness-of-fit test, except for DiaRem ( P <0.01), DiaBetter ( P <0.01), Hayes et al ( P = 0.03), Park et al ( P = 0.02), and Ramos-Levi et al' s ( P <0.01) models, all models had a satifactory fit results ( P >0.05). The P values of calibration results of the "ABCD" and IMS were 0.07 and 0.14, respectively. The predicted-to-observed ratios of the "ABCD" and IMS were 0.87 and 0.89, respectively. CONCLUSION: The prediction model IMS was recommended for clinical use because of excellent predictive performance, good statistical test results, and simple and practical design features.
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Diabetes Mellitus Tipo 2 , Laparoscopía , Obesidad Mórbida , Masculino , Humanos , Adulto , Femenino , Resultado del Tratamiento , Diabetes Mellitus Tipo 2/cirugía , Estudios Retrospectivos , Laparoscopía/métodos , Gastrectomía/métodos , Pérdida de Peso , Índice de Masa CorporalRESUMEN
Systematic evaluation of the consistency between circulating tumor DNA (ctDNA) in plasma and tumor tissue samples in mutations in non-small cell lung cancer (NSCLC) patients. To collect publicly published literature from numerous important international medical databases through computer retrieval. To compare the differences in literature data related to gene mutations between plasma ctDNA and tumor tissue samples, a meta-analysis was performed using Stata 12.0 software while taking into account the inclusion and exclusion criteria. This article includes a total of 15 research data and collected data reports from 15 groups of NSCLC patients. The results are displayed using tissue samples as the gold standard. The Pearson correlation coefficients of sensitivity and specificity were used to calculate rho=0.044, and P=0.893. The Q-test found poor homogeneity and high heterogeneity in sensitivity and specificity among research data from various literature studies (I2>50%, P<0.1). The area under the SROC curve is 0.97 (95% CI: 0.96~0.99). The small sample subgroup has high heterogeneity, and the combined diagnosis effect size is 26[6~111], lower than the large sample subgroup 185320 [0~2.7×1012]. When taking 200 as the cut-off point, the combined effect size of the small sample subgroup is 46 [12~183], still lower than that of the large sample subgroup 429 [52~3574]. From this, it can be concluded that the consistency of small-sample studies is higher than the quality of large-sample studies, and the heterogeneity is relatively low. From the perspective of mutation types, the heterogeneity of literature with EGFR gene mutations alone is higher than that of literature with non-EGFR mutations alone, and the consistency is lower. The consistency of using plasma ctDNA to detect mutations in NSCLC patients with tumor tissue samples is influenced by the type of mutation gene and sample size measured by the patient, and there is a significant bias in related studies.
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Carcinoma de Pulmón de Células no Pequeñas , Neoplasias Pulmonares , Humanos , Carcinoma de Pulmón de Células no Pequeñas/genética , Neoplasias Pulmonares/genética , Mutación/genética , Bases de Datos Factuales , PlasmaRESUMEN
BACKGROUND: Various prediction models of type 2 diabetes (T2D) remission have been externally verified internationally. However, long-term validated results after Roux-en-Y gastric bypass (RYGB) surgery are lacking. The best model for the Chinese population is also unknown. OBJECTIVES: To evaluate the prediction effect of various prediction models on the long-term diabetes remission after RYGB in the Chinese population and to provide reference for clinical use. SETTING: A retrospective clinical study at a university hospital. METHODS: We retrospectively analyzed Chinese population data 5 years after RYGB and externally validated 11 predictive models to evaluate the predictive effect of each model on long-term T2D remission after RYGB. RESULTS: We enrolled 84 patients. The mean body mass index was 41 kg/m2, and the percentage of excess weight loss (%EWL) was 72.3%. The mean glycated hemoglobin level was 8.4% preoperatively and decreased to 5.9% after 5 years. The 5-year postoperative complete and partial remission rates of T2D were 31% and 70.2%, respectively. The ABCD scoring model (sensitivity, 84%; specificity, 76%; area under the curve [AUC], .866) and the Panuzi et al. [34] study (sensitivity, 84%; specificity, 81%; AUC, .842) showed excellent results. In the Hosmer-Lemeshow goodness-of-fit test, calibration values for ABCD and Panuzi et al. [34] were .14 and .21, respectively. The predicted-to-observed ratios of ABCD and Panuzi et al. [34] were .83 and .88, respectively. CONCLUSIONS: T2D was relieved to varying degrees 5 years after RYGB in patients with obesity. The prediction models in ABCD and the Panuzi et al. [34] studies showed the best prediction effects. ABCD was recommended for clinical use because of excellent predictive performance, good statistical test results, and simple and practical design features.
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Background: Laparoscopic sleeve gastrectomy (LSG) is considered as an effective bariatric and metabolic surgery for patients with severe obesity. Chronic low-grade inflammation of adipose tissue is associated with obesity and obesity-related complications. Objective: This study intends to establish a nomogram based on inflammatory response-related methylation sites in intraoperative visceral adipose tissue (VAT) to predict excess weight loss (EWL)% at one-year after LSG. Methods: Based on EWL% at one-year after LSG, patients were divided into two groups: the satisfied group (group-A, EWL%≥50%) and the unsatisfied group (group-B, EWL%<50%). Next, we defined genes corresponding to the methylation sites in the 850 K methylation microarray as methylation-related genes (MRGs). We then took the intersection of MRGs and inflammatory response-related genes. After that, inflammatory response-related methylation sites were identified based on overlapping genes. Moreover, difference analysis was carried out to obtain inflammatory response-related differentially methylated sites (IRRDMSs) between group-A and group-B. LASSO analysis was used to identify the hub methylation sites. Finally, we developed a nomogram based on the hub methylation sites. Results: There were 26 patients in the study, with 13 in group-A and 13 in group-B. After data filtering and difference analysis, 200 IRRDMSs were identified (143 hypermethylated sites and 57 hypomethylated sites). Then, we identified three hub methylation sites (cg03610073, cg03208951, and cg18746357) by LASSO analysis and built a predictive nomogram (Area under the curve=0.953). Conclusion: The predictive nomogram based on three inflammatory-related methylation sites (cg03610073, cg03208951, and cg18746357) in intraoperative visceral adipose tissue can predict one-year EWL% after LSG effectively.
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Background: Many studies have reported that bariatric surgery may reduce postoperative cardiovascular risk in patient with obesity, but few have addressed this risk in the Chinese population. Objective: To assess the impact of bariatric surgery on cardiovascular disease (CVD) risk in the Chinese population using the World Health Organization (WHO) risk model, the Global risk model, and the Framingham Risk Score. Methods: We retrospectively analyzed data collected on patient with obesity who underwent bariatric surgery at our institution between March 2009 and January 2021. Their demographic characteristics, anthropometric variables, and glucolipid metabolic parameters were assessed preoperatively and at their 1-year postoperative follow-up. Subgroup analysis compared body mass index (BMI) < 35 kg/m2 and BMI ≥ 35 kg/m2, as well as gender. We used the 3 models to calculate their CVD risk. Results: We evaluated 61 patients, of whom 26 (42.62%) had undergone sleeve gastrectomy (SG) surgery and 35 (57.38%) Roux-en-Y gastric bypass (RYGB) surgery. Of the patients with BMI ≥ 35 kg/m2, 66.67% underwent SG, while 72.97% with BMI < 35 kg/m2 underwent RYGB. HDL levels were significantly higher at 12 months postoperatively relative to baseline. When the models were applied to calculate CVD risk in Chinese patients with obesity, the 1-year CVD risk after surgery were reduced lot compared with the preoperative period. Conclusion: Patient with obesity had significantly lower CVD risks after bariatric surgery. This study also demonstrates that the models are reliable clinical tools for assessing the impact of bariatric surgery on CVD risk in the Chinese population.
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Background: Older adults oftentimes suffer from the conditions in multiple physiologic systems, interfering with their daily function and thus contributing to physical frailty. The contributions of such multisystem conditions to physical frailty have not been well characterized. Methods: In this study, 442 (mean age = 71.4 ± 8.1 years, 235 women) participants completed the assessment of frailty syndromes, including unintentional weight loss, exhaustion, slowness, low activity, and weakness, and were categorized into frail (≥3 conditions), pre-frail (1 or 2 conditions), and robust (no condition) status. Multisystem conditions including cardiovascular diseases, vascular function, hypertension, diabetes, sleep disorders, sarcopenia, cognitive impairment, and chronic pain were assessed. Structural equation modeling examined the interrelationships between these conditions and their associations with frailty syndromes. Results: Fifty (11.3%) participants were frail, 212 (48.0%) were pre-frail, and 180 (40.7%) were robust. We observed that worse vascular function was directly associated with higher risk of slowness [standardized coefficient (SC) = -0.419, p < 0.001], weakness (SC = -0.367, p < 0.001), and exhaustion (SC = -0.347, p < 0.001). Sarcopenia was associated with both slowness (SC = 0.132, p = 0.011) and weakness (SC = 0.217, p = 0.001). Chronic pain, poor sleep quality, and cognitive impairment were associated with exhaustion (SC = 0.263, p < 0.001; SC = 0.143, p = 0.016; SC = 0.178, p = 0.004, respectively). The multinomial logistic regression showed that greater number of these conditions were associated with increased probability of being frail (odds ratio>1.23, p < 0.032). Conclusion: These findings in this pilot study provide novel insights into how multisystem conditions are associated with each other and with frailty in older adults. Future longitudinal studies are warranted to explore how the changes in these health conditions alter frailty status.
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The dynamic control of circularly polarized luminescence (CPL) has far-reaching significance in optoelectronics, information storage, and data encryption. Herein, we reported the reversible inversion of CPL in a coassembly supramolecular system consisting of chiral molecules L4, which contain two positively charged viologen units, and achiral ionic surfactant sodium dodecyl sulfate (SDS) by introducing achiral sulforhodamine B (SRB) dye molecules. The chirality of CPL in the coassemblies can be efficiently regulated and inverted by simply adjusting the amount of SRB. A series of experimental characterization, including optical spectroscopy, electron microscope, 1H NMR, and X-ray scattering measurements, suggested that SRB could coassemble with L4/SDS to establish a new stable L4/SDS/SRB supramolecular structure through electrostatic interactions. Moreover, the negative-sign CPL could revert to the positive-sign CPL if titanium dioxide (TiO2) nanoparticles were used to decompose SRB molecules. The evolution of the CPL inversion process could be cycled at least 5 times without a significant decline in CPL signals when SRB was refueled to the system. Our results provide a facile approach to dynamically regulating the handedness of CPL in a multiple-component supramolecular system via achiral species.
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Dynamic fluorophore 9,14-diphenyl-9,14-dihydrodibenzo[a,c]phenazine (DPAC) affords a new platform to produce diverse emission outputs. In this paper, a novel DPAC-containing crown ether macrocycle D-6 is synthesized and characterized. Host-guest interactions of D-6 with different ammonium guests produced a variety of fluorescence with hypsochromic shifts up to 130 nm, which are found to be affected by choice of solvent or guest and host/guest stoichiometry. Formation of supramolecular complexes were confirmed by UV-vis titration, 1H NMR and HRMS spectroscopy.
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BACKGROUND: Single-nucleotide polymorphisms (SNPs) associated with obesity predict laparoscopic Roux-en-Y gastric bypass (LRYGB) and biliopancreatic diversion with duodenal switch (BPD/DS) for weight loss with good efficiency. However, prediction of weight loss after laparoscopic sleeve gastrectomy using SNPs has not been well investigated. OBJECTIVES: To predict weight loss after laparoscopic sleeve gastrectomy using obesity-related SNPs and clinical variants in Chinese patients with body mass index (BMI) ≥ 32.5 kg/m2. METHODS: We detected 29 SNPs. Binary logistic regression was used to screen SNPs and clinical variables with predictive value. Receiver operating characteristic (ROC) curves were plotted for clinical variables, SNPs, and their combination, and areas under the ROC curve (AUC) were compared. Internal and external validation tests were performed. RESULTS: rs12535708, rs651821, and rs5082 were constructed as the genetic risk score (GRS). Preoperative BMI was constructed as the clinical risk score (CRS). Preoperative BMI and SNPs were constructed as the cumulative genetic risk score (CGRS). ROC curves of GRS, CRS, and CGRS showed that the optimal cutoffs were 0.831 (AUC = 0.840; sensitivity, 92.96%; specificity, 64.29%), 43.46 kg/m2 (AUC = 0.830; sensitivity, 76.06%; specificity, 85.71%), and 0.921 (AUC = 0.931; sensitivity, 77.46%; specificity, 92.86%), respectively. The AUC of CGRS was significantly greater than that of CRS (P < 0.05) and greater than GRS without statistical significance. CONCLUSION: In Chinese patients with BMI ≥ 32.5 kg/m2, GRS and CRS could predict weight loss success. However, CGRS was superior to GRS or CRS alone.
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Derivación Gástrica , Laparoscopía , Obesidad Mórbida , Humanos , Índice de Masa Corporal , Polimorfismo de Nucleótido Simple , Obesidad Mórbida/cirugía , Estudios Retrospectivos , Gastrectomía , Pérdida de Peso/genética , Obesidad/cirugía , China/epidemiología , Resultado del TratamientoRESUMEN
Purpose: To evaluate the predictive effect of the initial weight loss on the long-term weight loss in Chinese patients with a body mass index (BMI) ≥ 32.5 kg/m2 who underwent LSG. Patients and Methods: The follow-up was completed via phone or WeChat for outpatients and at the hospital for inpatients. We evaluated the BMI, percentage of excess weight loss (%EWL), and type 2 diabetes mellitus, hypertension, and hyperlipidemia statuses. Linear and logistic regression analyses were performed on the relationship between the initial and long-term weight loss. The optimal cut-off value was determined by receiver operating characteristic (ROC) curve analysis. Results: We enrolled 307 patients, with a median preoperative BMI of 39.68 (35.68, 45.47) kg/m2. %EWL ≥ 50% was regarded as successful weight loss, and 76.55% of the patients lost their weight successfully. (Reviewer #1, comment #4) %EWL at 6 months and 5 years were positively correlated (P < 0.001). Further, the following linear equation could express the relationship: (%EWL5 years = 29.193 + 0.526 × %EWL6 months). %EWL ≥ 58.57% at 6 months was the best predictor of successful weight loss at 5 years after LSG (Reviewer #1, comment #5) (sensitivity, 73.62%; specificity, 73.61%; AUC value, 0.780). Internal verification of the prediction model revealed satisfactory results in terms of discrimination and calibration. Conclusion: In Chinese patients with BMI ≥ 32.5 kg/m2 who underwent LSG, %EWL at 6 months and 5 years were correlated. %EWL ≥ 58.57% at 6 months was a predictor of successful long-term weight loss.
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Many discharged COVID-19 patients affected by sequelae experience reduced quality of life leading to an increased burden on the healthcare system, their families and society at large. Possible pathophysiological mechanisms of long COVID include: persistent viral replication, chronic hypoxia and inflammation. Ongoing vascular endothelial damage promotes platelet adhesion and coagulation, resulting in the impairment of various organ functions. Meanwhile, thrombosis will further aggravate vasculitis contributing to further deterioration. Thus, long COVID is essentially a thrombotic sequela. Unfortunately, there is currently no effective treatment for long COVID. This article summarizes the evidence for coagulation abnormalities in long COVID, with a focus on the pathophysiological mechanisms of thrombosis. Extracellular vesicles (EVs) released by various types of cells can carry SARS-CoV-2 through the circulation and attack distant tissues and organs. Furthermore, EVs express tissue factor and phosphatidylserine (PS) which aggravate thrombosis. Given the persistence of the virus, chronic inflammation and endothelial damage are inevitable. Pulmonary structural changes such as hypertension, embolism and fibrosis are common in long COVID. The resulting impaired lung function and chronic hypoxia again aggravates vascular inflammation and coagulation abnormalities. In this article, we also summarize recent research on antithrombotic therapy in COVID-19. There is increasing evidence that early anticoagulation can be effective in improving outcomes. In fact, persistent systemic vascular inflammation and dysfunction caused by thrombosis are key factors driving various complications of long COVID. Early prophylactic anticoagulation can prevent the release of or remove procoagulant substances, thereby protecting the vascular endothelium from damage, reducing thrombotic sequelae, and improving quality of life for long-COVID patients.
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Tratamiento Farmacológico de COVID-19 , COVID-19 , Trombosis , Anticoagulantes/uso terapéutico , COVID-19/complicaciones , Humanos , Hipoxia , Inflamación/complicaciones , Calidad de Vida , SARS-CoV-2 , Trombosis/etiología , Trombosis/prevención & control , Síndrome Post Agudo de COVID-19RESUMEN
Objective: At present, renal injury caused by sepsis seriously endangers the health of patients. Our paper proposed to study the protective effects of meloxicam (Mel) in sepsis-induced acute kidney injury (SAKI) and the underlying mechanisms. Methods: The in vitro and in vivo models of SAKI were established using lipopolysaccharide (LPS). Mel was injected intraperitoneally at 60 mg/kg into male C57BL/6 mice 4 hours before LPS injection (10 mg/kg). The HK-2 cells were treated with LPS (1 µg/mL) and Mel (40 µM). The renal function and renal pathological changes as well as renal inflammation and apoptosis were detected in SAKI mice. The inflammation and apoptosis of HK-2 cells induced by LPS were also detected. Results: The treatment of Mel significantly decreased the elevated levels of serum creatinine (Scr) and blood urea nitrogen (BUN) in SAKI mice. In addition, the results of HE staining suggested that Mel significantly reduced kidney damage in SAKI mice. Consistently, Mel reduced the expression of LPS-induced kidney injury markers (NGAL and KIM-1). Moreover, LPS induced the expression of inflammatory cytokines (IL-1ß, IL-6, and TNF-α) in the kidney, which can be reduced by Mel. Furthermore, Mel effectively reduced the number of apoptotic cells and inhibited the expression of proapoptotic-related proteins (cleaved Caspase-3 and Bax) but increased the antiapoptotic-related protein (Bcl-2) in the kidneys of SAKI mice. Mechanistically, Mel inhibited the phosphorylation of P65 but induced the phosphorylation of AKT and the expression of glycoprotein B of nonmetastatic melanoma (GPNMB). However, knocking down GPNMB can eliminate the anti-inflammatory and antiapoptotic effects of Mel. Conclusion: Mel alleviated sepsis-induced kidney injury by inhibiting kidney inflammation and apoptosis via upregulating GPNMB.
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Organism-inspired hollow structures are attracting increasing interest for the construction of various bionic functional hollow materials. Next-generation self-evolution hollow materials tend to combine simple synthesis, high mechanical strength, and regular shape. In this study, we designed and synthesized a novel dry-network polythiourethane thermoset with excellent mechanical performance. The polymer film could evolve into a neat and well-organized object with a macroscopic hollow interior structure after being immersed in an aqueous NaOH solution. The self-evolution hollow structure originated from a hydrogen-bonded polymer network, which was later transformed into a network bearing both hydrogen bonds and ionic bonds. The swelling and thickness growth of this material could be controlled by the NaOH concentration and the immersion time. This unique self-evolution behavior was further utilized to produce a series of macroscopic 3D hollow-containing molds, which could be potentially applied in the production of smart materials.