Accurate multi-objective prediction of CO2 emission performance indexes and industrial structure optimization using multihead attention-based convolutional neural network.

The establishment of specific targets for the global carbon peaking and neutrality raises urgent requirements for prediction of CO2 emission performance indexes (CEPIs) and industrial structure optimization. However, accurate multi-objective prediction of CEPIs is still a knotty problem. In the present study, multihead attention-based convolutional neural network (MHA-CNN) model was proposed for accurate prediction of 4 CEPIs and further provided the rational suggestions for further industrial structure optimization. The proposed MHA-CNN model introduces deep learning mechanism with efficient resolution strategies for training model overfitting, feature extraction, and self-supervised learning to acquire the adaptability for CEPIs. Multihead attention (MHA) mechanism plays important roles in influence weight interpretation of variables to facilitate the prediction performance of CNN on CEPIs. The MHA-CNN model presented its overwhelmingly superior performance to CNN model and long short-term memory (LSTM) model, two frequently-used models, in multi-objective prediction of CEPIs using 8 influence variables, which highlighted advantages of MHA module in multi-dimensional feature extraction. Additionally, contributions of influence variables to CEPIs based on MHA analyses presented relatively high consistency with the geographical distribution analyses, indicating the excellent capacity of the MHA module in variable weights identification and contribution dissection. Based on the more accurate prediction results by MHA-CNN than those by CNN and LSTM model, the increase in the tertiary industry and the decreases in the first and secondary industries are conducive to improvement of total-factor carbon emission efficiency and further enhancement of effective energy utilization in regions with inefficient carbon emissions. This study provides insights towards the critical roles of the proposed MHA-CNN model in accurate multi-objective prediction of CEPIs and further industrial structure optimization for improvement of total-factor carbon emission efficiency.

Free nitrous acid prediction in ANAMMOX process using hybrid deep neural network model.

Free nitrous acid (FNA) is a critical metric for stabilization of ANAMMOX but can not be directly and immediately measured by sensors or chemical measurement method, which hinders the effective management and operation for ANAMMOX. This study focuses on FNA prediction using hybrid model based on temporal convolutional network (TCN) combined with attention mechanism (AM) optimized by multiobjective tree-structured parzen estimator (MOTPE), called MOTPE-TCNA. A case study in an ANAMMOX reactor is carried out. Results show that nitrogen removal rate (NRR) is highly correlated with FNA concentration, indicating that it can forecast the operational status by predicting FNA. Then, MOTPE successfully optimizes the hyperparameters of TCN, helping TCN achieve a high prediction accuracy, and AM furtherly improves model accuracy. MOTPE-TCNA obtains the highest prediction accuracy, whose R2 value gets 0.992, increasing 1.71-11.80% compared to other models. As a deep neural network model, MOTPE-TCNA has more advantages than traditional machine learning methods in FNA prediction, which is beneficial to maintain the stable operation and easy control for ANAMMOX process.

Metformin Inhibits Abdominal Aortic Aneurysm Formation through the Activation of the AMPK/mTOR Signaling Pathway.

BACKGROUND AND OBJECTIVE: Epidemiological evidence suggests that the antidiabetic drug metformin (MET) can also inhibit abdominal aortic aneurysm (AAA) formation. However, the underlying protective mechanism remains unknown. It has been reported that phosphorylated AMP-activated protein kinase (AMPK) levels are significantly lower in AAA tissues than control aortic tissues. AMPK activation can inhibit the downstream signaling molecule called mechanistic target of rapamycin (mTOR), which has also been reported be upregulated in thoracic aneurysms. Thus, blocking mTOR signaling could attenuate AAA progression. MET is a known agonist of AMPK. Therefore, in this study, we investigated if MET could inhibit formation of AAA by activating the AMPK/mTOR signaling pathway. MATERIALS AND METHODS: The AAA animal model was induced by intraluminal porcine pancreatic elastase (PPE) perfusion in male Sprague Dawley rats. The rats were treated with MET or compound C (C.C), which is an AMPK inhibitor. AAA formation was monitored by serial ultrasound. Aortas were collected 4 weeks after surgery and subjected to immunohistochemistry, Western blot, and transmission electron microscopy analyses. RESULTS: MET treatment dramatically inhibited the formation of AAA 4 weeks after PPE perfusion. MET reduced the aortic diameter, downregulated both macrophage infiltration and matrix metalloproteinase expression, decreased neovascularization, and preserved the contractile phenotype of the aortic vascular smooth muscle cells. Furthermore, we detected an increase in autophagy after MET treatment. All of these effects were reversed by the AMPK inhibitor C.C. CONCLUSION: This study demonstrated that MET activates AMPK and suppresses AAA formation. Our study provides a novel mechanism for MET and suggests that MET could be potentially used as a therapeutic candidate for preventing AAA.

Dietary inflammatory index and depression: a meta-analysis.

OBJECTIVE: The purpose of the present meta-analysis was to evaluate the association between the inflammatory potential of diet, determined by the dietary inflammatory index (DII®) score, and depression. DESIGN: Systematic review and meta-analysis. SETTING: A comprehensive literature search was conducted in PubMed, Web of Science and EMBASE databases up to August 2018. All observational studies that examined the association of the DII score with depression/depressive symptoms were included. SUBJECTS: Four prospective cohorts and two cross-sectional studies enrolling a total of 49 584 subjects. RESULTS: Overall, individuals in the highest DII v. the lowest DII category had a 23 % higher risk of depression (risk ratio (RR)=1·23; 95 % CI 1·12, 1·35). When stratified by study design, the pooled RR was 1·25 (95 % CI 1·12, 1·40) for the prospective cohort studies and 1·16 (95 % CI 0·96, 1·41) for the cross-sectional studies. Gender-specific analysis showed that this association was observed in women (RR=1·25; 95 % CI 1·09, 1·42) but was not statistically significant in men (RR=1·15; 95 % CI 0·83, 1·59). CONCLUSIONS: The meta-analysis suggests that pro-inflammatory diet estimated by a higher DII score is independently associated with an increased risk of depression, particularly in women. However, more well-designed studies are needed to evaluate whether an anti-inflammatory diet can reduce the risk of depression.

Sarcopenia defined by the psoas muscle mass or quality is associated with poor survival in patients with aortic aneurysm undergoing surgery: A meta-analysis.

BACKGROUND: The impact of sarcopenia estimated by the skeletal muscle mass or quality on survival remains controversial in patients with aortic aneurysm. This meta-analysis aimed to assess the association between sarcopenia defined by the psoas muscle mass or quality and all-cause mortality in patients with aortic aneurysm. METHODS: We comprehensively searched PubMed, Web of Science, and Embase databases until December 31, 2022. Studies investigating the association of CT-derived psoas muscle mass (psoas muscle area [PSA] and psoas muscle index [PMI]) or quality (lean PSA [LPSA]) with all-cause mortality in patients with aortic aneurysm undergoing surgery were included. RESULTS: Eighteen studies reporting on 19 articles, enrolling 4767 patients were identified. A comparison of the bottom with the top psoas muscle mass, the pooled adjusted hazard ratios (HR) of all-cause mortality was 2.34 (95% confidence intervals [CI] 1.58-3.47). Low psoas muscle mass was associated with an increased risk of all-cause mortality when defined by the PSA (HR 2.01; 95% CI 1.42-2.75) or PMI (HR 2.37; 95% CI 1.24-4.55). Per 1 cm2 PMA increase conferred a 10% reduction in all-cause mortality. Patients with bottom LPMA had an increased risk of all-cause mortality (HR 3.27; 95% CI 1.90-5.60). Each 100 cm2 × HU LPMA increase conferred a 15% reduction in all-cause mortality. CONCLUSIONS: Sarcopenia defined by the low psoas muscle mass or quality independently predicts all-cause mortality in patients with aortic aneurysm. However, the overall certainty of evidence for the categorical analysis of psoas muscle mass was downgraded by the presence of publication bias and significant heterogeneity.

Visible-Light-Promoted C(sp3)-C(sp3) Cross-Coupling of Amino Acids and Aryl Trifluoromethyl Ketones Through Simultaneous Decarboxylation and Defluorination.

A photoredox-catalyzed approach for the difluoroalkylation of amino acids was achieved through simultaneous decarboxylation and defluorination processes. This innovative protocol employs commonly available amino acids and trifluoroacetophenones as the primary starting materials, eliminating the necessity for preactivation. This strategy has enabled the synthesis of several difluoroketone functionalized amines in moderate to impressive yields. These synthesized compounds are presented as foundational molecules for subsequent modification. The underlying mechanism for the transformation is anchored in a single electron transfer (SET) radical pathway.

Predictive value of abnormal ankle-brachial index in patients with diabetes: A meta-analysis.

AIMS: This meta-analysis aimed to examine the association of abnormal ankle brachial index (ABI) with adverse prognosis in patients with diabetes. METHODS: We systematically searched PubMed and Embase databases from inception to October 31, 2020 for observational studies investigating the predictive utility of abnormal ABI in patients with diabetes. The normal ABI is usually defined by 0.9-1.3 or 1.4. RESULTS: Data were collected from 9 studies involving 9673 patients. When compared with the reference normal ABI, abnormal ABI was associated with a higher risk of cardiovascular mortality (risk ratio [RR] 1.98; 95% confidence intervals [CI] 1.66-2.37), all-cause mortality (RR 2.12; 95% CI 1.81-2.49), and major adverse cardiovascular events ([MACEs] RR 2.37; 95% CI 1.73-3.26). Subgroup analysis indicated that the pooled RR of cardiovascular mortality was similar in individuals with abnormally low ABI (RR 1.98; 95% CI 1.64-2.39) or high ABI (RR 2.00; 95% CI 1.12-3.59). CONCLUSIONS: Abnormal ABI independently predicts subsequent risk of cardiovascular or all-cause mortality and MACEs in patients with diabetes. However, the predictive role of abnormal ABI is largely dominated by the low ABI rather than the high ABI.

[Expression of proto-oncogene Wip1 in breast cancer and its clinical significance].

OBJECTIVE: To investigate the expression of proto-oncogene Wip1 in breast cancer tissue and its clinical significance. METHODS: Through the uses of semi-RT-PCR, immunohistochemical technique and Western blot, the specimens from 70 patients of breast cancer and 20 normal controls were detected for Wip1 mRNA and protein expression. At the same time, the authors analyzed the relations between the expression of Wip1 in human breast cancer and different clinical pathologic parameters. RESULTS: RT-PCR: The values of gene expression of Wip1 mRNA in breast cancer tissue, pericancerous tissue and normal breast tissue were 0.715 +/- 0.087, 0.175 +/- 0.021 and 0.154 +/- 0.022 respectively. Thus the value of gene expression in breast cancer tissue was significantly higher than that in pericancerous tissue or normal breast tissue (P < 0.01). Immunohistochemistry: The high expression rates of Wip1 protein in breast cancer tissue, pericancerous tissue and normal breast tissue were 62.9% (44/70), 2.9% (2/70) and 0 (0/20) respectively and there was a significant difference among these three different tissues (P < 0.01). Western blot: The relative contents of Wip1 protein in breast cancer tissue, pericancerous tissue and normal breast tissue were 0.688 +/- 0.151, 0.251 +/- 0.043 and 0.234 +/- 0.044 respectively. The relative content of Wip1 protein in breast cancer tissue was significantly higher than that in pericancerous tissue or normal breast tissue (P < 0.01). The high expression of Wip1 protein was negatively correlated with the expression of p53, but it had nothing to do with tumor size, age, tumor staging, axillary lymph node metastasis and expressions of ER and PR. CONCLUSION: The high expression of Wip1 mRNA and its protein in breast cancer tissue may promote the growth of breast cancer. Wip1 may become a new target for therapy of breast cancer.

[Deep venous thrombosis of lower extremities: effects of different treatment on the incidence of pulmonary embolism].

OBJECTIVE: To investigate the effects of the different treatments of deep venous thrombosis (DVT) of lower extremities on the incidence of the pulmonary embolism (PE). METHODS: 201 patients (97 males and 104 females, mean age 60.4 years ranged from 24 to 83) from August 2002 to June 2008 with DVT were retrospectively reviewed and divided into 3 groups based on different treatment, including anticoagulants plus thrombolytics alone (group 1), thrombectomy plus anticoagulants plus thrombolytics (group 2) and anticoagulants plus thrombolytics after delivery of inferior vena cava (IVC) filter (group 3) respectively. One hundred and seventy-four cases had left lower limb DVT, 24 cases had right lower limb DVT and 3 cases had both sides of lower limb DVT. Different incidence of PE in different period (7-14 d in hospital and follow-up after discharge) were calculated. Effects of the three different treatment methods of DVT on the incidence of PE were studied. RESULTS: For in-patients, the prevalence of symptomatic PE was 2.8% (3/107) in the group of receiving anticoagulants plus thrombolytics alone, but in the other two groups, no symptomatic PE happened. There was no significant difference in incidence of symptomatic PE among the 3 groups (P=0.425). For patients discharged, after 6 to 72-month follow-up (mean 24-month), we found that no PE happened in group 1 and group 2, while in group 3, the incidence of PE was 2.4% (1/42). There was also no significant difference (P=0.656) among 3 groups. CONCLUSIONS: There is no significant difference in relation to the incidence of PE in these 3 groups. Therefore vena cava filter implantation should be restricted to optimal indication.

Uric acid in aortic dissection: A meta-analysis.

BACKGROUND: Studies on the serum uric acid levels in patients with aortic dissection have yielded conflicting results. OBJECTIVE: To compare the difference in serum uric acid (SUA) levels between aortic dissection patients and controls by meta-analysis. METHODS: Electronic literature search was conducted in PubMed, Embase, CKNI, CBM, Wanfang, and VIP databases until January 31, 2018. All observational studies that investigated SUA levels in aortic dissection patients and controls were included. Weighted mean difference (WMD) with 95% confidence intervals (CI) was used to summarize the difference in SUA levels between aortic dissection and control group. RESULTS: A total of seven case-control studies involving 1197 patients and 1193 controls were included. Pooled analysis showed that SUA levels were significantly higher in aortic dissection patients compared with those in the controls (WMD 58.22 µmol/L; 95% CI 26.71-89.73) in a random effect model. No significant difference (WMD 9.94 µmol/L; 95% CI -17.89-37.76) was observed in SUA levels between Stanford type A and Stanford type B aortic dissection. CONCLUSIONS: This meta-analysis provides evidence that SUA levels are significantly higher among patients with aortic dissection than those in controls. Elevated SUA levels may contribute to the pathogenesis of aortic dissection. Further large clinical studies to investigate whether SUA levels are an independently risk factor for aortic dissection are warranted.