Learning global dependencies and multi-semantics within heterogeneous graph for predicting disease-related lncRNAs.

MOTIVATION: Long noncoding RNAs (lncRNAs) play an important role in the occurrence and development of diseases. Predicting disease-related lncRNAs can help to understand the pathogenesis of diseases deeply. The existing methods mainly rely on multi-source data related to lncRNAs and diseases when predicting the associations between lncRNAs and diseases. There are interdependencies among node attributes in a heterogeneous graph composed of all lncRNAs, diseases and micro RNAs. The meta-paths composed of various connections between them also contain rich semantic information. However, the existing methods neglect to integrate attribute information of intermediate nodes in meta-paths. RESULTS: We propose a novel association prediction model, GSMV, to learn and deeply integrate the global dependencies, semantic information of meta-paths and node-pair multi-view features related to lncRNAs and diseases. We firstly formulate the global representations of the lncRNA and disease nodes by establishing a self-attention mechanism to capture and learn the global dependencies among node attributes. Second, starting from the lncRNA and disease nodes, respectively, multiple meta-pathways are established to reveal different semantic information. Considering that each meta-path contains specific semantics and has multiple meta-path instances which have different contributions to revealing meta-path semantics, we design a graph neural network based module which consists of a meta-path instance encoding strategy and two novel attention mechanisms. The proposed meta-path instance encoding strategy is used to learn the contextual connections between nodes within a meta-path instance. One of the two new attention mechanisms is at the meta-path instance level, which learns rich and informative meta-path instances. The other attention mechanism integrates various semantic information from multiple meta-paths to learn the semantic representation of lncRNA and disease nodes. Finally, a dilated convolution-based learning module with adjustable receptive fields is proposed to learn multi-view features of lncRNA-disease node pairs. The experimental results prove that our method outperforms seven state-of-the-art comparing methods for lncRNA-disease association prediction. Ablation experiments demonstrate the contributions of the proposed global representation learning, semantic information learning, pairwise multi-view feature learning and the meta-path instance encoding strategy. Case studies on three cancers further demonstrate our method's ability to discover potential disease-related lncRNA candidates. CONTACT: zhang@hlju.edu.cn or peiliangwu@ysu.edu.cn. SUPPLEMENTARY INFORMATION: Supplementary data are available at Briefings in Bioinformatics online.

Graph Reasoning Method Based on Affinity Identification and Representation Decoupling for Predicting lncRNA-Disease Associations.

An increasing number of studies have shown that dysregulation of lncRNAs is related to the occurrence of various diseases. Most of the previous methods, however, are designed based on homogeneity assumption that the representation of a target lncRNA (or disease) node should be updated by aggregating the attributes of its neighbor nodes. However, the assumption ignores the affinity nodes that are far from the target node. We present a novel prediction method, GAIRD, to fully leverage the heterogeneous information in the network and the decoupled node features. The first major innovation is a random walk strategy based on width-first searching and depth-first searching. Different from previous methods that only focus on homogeneous information, our new strategy learns both the homogeneous information within local neighborhoods and the heterogeneous information within higher-order neighborhoods. The second innovation is a representation decoupling module to extract the purer attributes and the purer topologies. Third, a module based on group convolution and deep separable convolution is developed to promote the pairwise intrachannel and interchannel feature learning. The experimental results show that GAIRD outperforms comparing state-of-the-art methods, and the ablation studies prove the contributions of major innovations. We also performed case studies on 3 diseases to further demonstrate the effectiveness of the GAIRD model in applications.

Effects of TIMP-2 Polymorphisms on Retinopathy of Prematurity Risk, Severity, Recurrence, and Treatment Response.

Tissue inhibitors of metalloproteinases (TIMPs) play a crucial role in endogenous angiogenesis besides the regulation of matrix metalloproteinase (MMP) activity. Associations between TIMP-2 gene polymorphisms and the risk of retinopathy of prematurity (ROP) were examined. Premature infants born between 2009 and 2018 were included. Five single-nucleotide polymorphisms (SNPs) of TIMP-2 were analyzed with real-time polymerase chain reaction (PCR). Multivariate logistic regression was applied to model associations between TIMP-2 polymorphisms and ROP susceptibility and severity. The GA+AA genotype in individuals with the TIMP-2 polymorphism of rs12600817 was associated with a higher risk of ROP (odds ratio [OR]: 1.518, 95% confidence interval [CI]: 1.028-2.242) compared with their wild-type genotypes. The AA genotype (OR: 1.962, 95% CI: 1.023-3.762) and the AA+GA genotype (OR: 1.686, 95% CI: 1.030-2.762) in individuals with the rs12600817 polymorphism had higher risks of severe, treatment-requiring ROP relative to their wild-type counterparts. In patients with treatment-requiring ROP, the AG+GG genotypes in the TIMP-2 polymorphism of rs2889529 were correlated with the treatment response (p = 0.035). The TIMP-2 polymorphism of rs12600817 help in predicting ROP risks in preterm infants, while the polymorphism of rs2889529 can serve as a genetic marker in evaluating the ROP treatment response.

Recurrent pneumothorax and intrapulmonary cavitary lesions in a male patient with vascular Ehlers-Danlos syndrome and a novel missense mutation in the COL3A1 gene: a case report.

BACKGROUND: Vascular Ehlers-Danlos syndrome (vEDS) is a rare autosomal dominant hereditary collagen disease caused by a defect or deficiency in the pro-α1 chain of type III procollagen encoded by the COL3A1 gene. Patients with vEDS rarely present with multiple pneumothoraces. The clinical features of this disease are not familiar to clinicians and are easily missed. We report a patient with a novel missense mutation in the COL3A1 gene (NM_000090.3: c.2977G > A) and hope to provide clinicians with valuable information. CASE PRESENTATION: We reported the case of a young man presenting with frequent episodes of pneumothorax and intrapulmonary cavities and nodular lesions without arterial or visceral complications. His skin was thin and transparent, and the joints were slightly hypermobile. Whole-exome sequencing (chip capture high-throughput sequencing) revealed a heterozygous missense mutation in exon 41 of the COL3A1 gene (NM_000090.3: c.2977G > A), confirming the diagnosis of vEDS. vEDS remains a very rare and difficult diagnosis to determine. CONCLUSION: When a patient presents with recurrent pneumothorax, intrapulmonary cavities and nodular lesions, thin and transparent skin, and hypermobile joints, clinicians should consider the diagnosis of vEDS.

L6H9 attenuates LPS-induced acute lung injury in rats through targeting MD2.

Acute lung injury (ALI) is a clinical syndrome characterized by respiratory failure and acute inflammatory response. Myeloid differentiation protein 2 (MD2) has been reported to play a pivotal role in the recognition of LPS and LPS-mediates inflammatory response. There have been no clinically effective therapeutic drugs for ALI. L6H9, an inhibitor of MD2, showed anti-inflammatory effects and cardiac protective activity. However, its effect on ALI has not been elucidated. In this study, intratracheal instillation of LPS was employed to induce ALI in rats. L6H9 pretreatment attenuates LPS-induced pathological variations in lung tissue and pulmonary edema. LPS instillation enhanced lung microvascular permeability, thereby causing inflammatory cells flow into bronchoalveolar lavage fluid (BALF). However, L6H9 inhibited the LPS-induced upregulation of total protein concentration and the number of inflammatory cells in BALF. In the meantime, macrophages infiltration in lung tissue induced by LPS was also mitigated by L6H9 treatment. Furthermore, L6H9 suppressed LPS-induced inflammatory cytokines expression in BALF, serum, and lung tissue. It is noteworthy that LPS-induced MD2/TLR4 complex formation was inhibited by L6H9 in lung tissue. On the whole, these results show that L6H9 can attenuate LPS-induced ALI in vivo by targeting MD2. Our study provide new candidate for the treatment of ALI.

Baicalin attenuates chronic hypoxia-induced pulmonary hypertension via adenosine A2A receptor-induced SDF-1/CXCR4/PI3K/AKT signaling.

BACKGROUND: Baicalin, an important flavonoid in Scutellaria baicalensis Georgi extracts, exerts a variety of pharmacological effects. In this study, we explored the effects of baicalin on chronic hypoxia-induced pulmonary arterial hypertension (PAH) and investigated the mechanism underlying these effects. Moreover, we examined whether the inflammatory response was mediated by the A2A receptor (A2AR) and stromal cell-derived factor-1 (SDF-1)/C-X-C chemokine receptor type 4 (CXCR4)-induced phosphatidyl inositol-3-kinase (PI3K) signaling in vivo. METHODS: We established a hypoxia-induced pulmonary hypertension (HPH) mouse model by subjecting wild-type (WT) and A2AR knockout (A2AR-/-) animals to chronic hypoxia, and we examined the effects of a 4-week treatment with baicalin or the A2AR agonist CGS21680 in these animals. Invasive hemodynamic parameters, the right ventricular hypertrophy index, pulmonary congestion, the pulmonary arterial remodeling index, blood gas parameters, A2AR expression, and the expression of SDF-1/CXCR4/PI3K/protein kinase B (PKB; AKT) signaling components were measured. RESULTS: Compared with WT mice, A2AR-/- mice exhibited increased right ventricular systolic pressure (RVSP), right ventricle-to-left ventricle plus septum [RV/(LV + S)] ratio, RV weight-to-body weight (RV/BW) ratio, and lung wet weight-to-body weight (Lung/BW) ratio in the absence of an altered mean carotid arterial pressure (mCAP). These changes were accompanied by increases in pulmonary artery wall area and thickness and reductions in arterial oxygen pressure (PaO2) and hydrogen ion concentration (pH). In the HPH model, A2AR-/- mice displayed increased CXCR4, SDF-1, phospho-PI3K, and phospho-AKT expression compared with WT mice. Treating WT and A2AR-/- HPH mice with baicalin or CGS21680 attenuated the hypoxia-induced increases in RVSP, RV/(LV + S) and Lung/BW, as well as pulmonary arterial remodeling. Additionally, baicalin or CGS21680 alone could reverse the hypoxia-induced increases in CXCR4, SDF-1, phospho-PI3K, and phospho-AKT expression. Moreover, baicalin improved the hypoxemia induced by 4 weeks of hypoxia. Finally, we found that A2AR levels in WT lung tissue were enhanced by hypoxia and that baicalin up-regulated A2AR expression in WT hypoxic mice. CONCLUSIONS: Baicalin exerts protective effects against clinical HPH, which are partly mediated through enhanced A2AR activity and down-regulated SDF-1/CXCR4-induced PI3K/AKT signaling. Therefore, the A2AR may be a promising target for baicalin in treating HPH.

Salidroside attenuates hypoxia-induced pulmonary arterial smooth muscle cell proliferation and apoptosis resistance by upregulating autophagy through the AMPK-mTOR-ULK1 pathway.

BACKGROUND: Recent studies have shown that both adenosine monophosphate activated protein kinase (AMPK) and the mammalian target of rapamycin (mTOR) are energy sensors and are related to autophagy. Our recent reports have shown that salidroside can exert protective effects against hypoxia-induced pulmonary arterial smooth muscle cell (PASMC) proliferation and apoptosis resistance through the AMPK pathway. This study aims to explore the relationship among AMPK, mTOR and ULK1 in PASMCs under hypoxic conditions and to investigate whether the protective effects of salidroside are related to the autophagic cell death pathway. METHODS: Rat PASMCs were cultured and divided into five groups: the normoxia, hypoxia, hypoxia + MHY1485 (mTOR agonist), hypoxia + rapamycin (mTOR inhibitor) and hypoxia + salidroside groups. Hypoxic cells were treated as indicated for 24 h. Cell viability was evaluated by the CCK-8 assay. Cell apoptosis was measured by the TUNEL assay. The autophagy flux of PASMCs was evaluated with tandem mRFP-GFP fluorescence microscopy. Autophagosomes were detected by electron microscopy. Protein expression of LC3, p62, AMPK, P-AMPK (Thr 172), P-ULK1 (Ser 555 and Ser 317), mTOR, P-mTOR (Ser 2448), ULK1 and P-ULK1 (Ser 757) was detected by western blot assay. RESULTS: PASMC proliferation and apoptosis resistance were observed under hypoxic conditions. Autophagy flux, the number of autophagosomes and the LC3II/LC3I ratio were increased in the hypoxia group compared with the normoxia group, whereas p62 expression was decreased. Treatment with rapamycin or salidroside reversed hypoxia-induced PASMC proliferation and apoptosis resistance and further increased autophagy flux, autophagosome levels and the LC3II/LC3I ratio but decreased p62 expression. Treatment with MHY1485 reversed hypoxia-induced PASMC apoptosis resistance and decreased autophagy flux as well as increased autophagosome levels, the LC3II/LC3I ratio and p62 expression. P-AMPK (Thr 172) and P-ULK1 (Ser 555) of the AMPK-ULK1 pathway were increased in the hypoxia group and were further increased in the salidroside group. Rapamycin and MHY1485 had no effect on either P-AMPK (Thr 172) or P-ULK1 (Ser 555). Phosphorylation of ULK1 at serine 317 did not significantly affect the five groups. Furthermore, P-mTOR (Ser 2448) and P-ULK1 (Ser 757) of the AMPK-mTOR-ULK1 pathway were decreased in the hypoxia group and were further decreased in the salidroside group. MHY1485 increased the expression of both P-mTOR(Ser 2448) and P-ULK1(Ser 757), whereas rapamycin had the opposite effect. CONCLUSIONS: Salidroside might inhibit hypoxia-induced PASMC proliferation and reverse apoptosis resistance via the upregulation of autophagy through both the AMPKα1-ULK1 and AMPKα1-mTOR-ULK1 pathways.

Baicalin attenuates bleomycin-induced pulmonary fibrosis via adenosine A2a receptor related TGF-ß1-induced ERK1/2 signaling pathway.

BACKGROUND: Baicalin has been reported to have anti-fibrosis effect; however, its mechanism still remains to be elucidated. Adenosine A2a receptor (A2aR) is a novel inflammation regulator, and transforming growth factor-ß1 (TGF-ß1)-induced extracellular signal regulated kinase1/2 (ERK1/2) signaling pathway plays an important role in idiopathic pulmonary fibrosis (IPF). This study was to explore the relationship of A2aR and TGF-ß1-induced ERK1/2 in bleomycin (BLM)-induced pulmonary fibrosis in mice, and to investigate whether A2aR mediate the anti-fibrosis effect of Baicalin on BLM-induced pulmonary fibrosis. METHODS: The A2aR-/- and A2aR+/+ mice were respectively divided into three groups: control group, model group, baicalin group. Pulmonary fibrosis was induced in mice of model groups by intratracheal instillation of bleomycin, and baicalin was administered in mice of baicalin groups daily for 28 days. Histopathological and ultrastructural changes of lung tissues were evaluated. Lung coefficient and the levels of hydroxyproline (HYP) in lung tissues were measured at the same time. The levels of serum TGF-ß1 were measured by ELISA. The expression of TGF-ß1, ERK1/2, p-ERK1/2 and A2aR were detected by western blot and immunohistochemical staining techniques. RESULTS: Severe lung fibrosis was observed in the bleomycin-treated mice on day 28. The histopathological findings and collagen content of lung tissues were much severer/higher in A2aR-/- mice than in A2aR+/+ mice. We also showed that TGF-ß1 and p-ERK1/2 were upregulated in bleomycin-treated mice and expressed higher in A2aR-/- mice compared to A2aR+/+ mice. Besides, bleomycin-treated A2aR+/+ mice had increased A2aR level in lungs. However, long-term treatment with baicalin in A2aR-/- and A2aR+/+ mice significantly ameliorated the histopathological changes in lungs. Moreover, Increased TGF-ß1 and p-ERK1/2 expressions in bleomycin-treated A2aR-/- and A2aR+/+ mice were obviously diminished by baicalin. The baicalin-treated A2aR-/- mice had severer lung fibrosis and higher expressions of TGF-ß1 and p-ERK1/2 than A2aR+/+ mice. Baicalin has also upregulated the expression of A2aR in A2aR+/+ mice. CONCLUSIONS: Genetic inactivation of A2aR exacerbated the pathological processes of bleomycin-induced pulmonary fibrosis. Together, baicalin could inhibit BLM-induced pulmonary fibrosis by upregulating A2aR, suggesting A2aR as a therapeutic target of baicalin for the treatment of pulmonary fibrosis.

Diagnosis and therapy of giant epidermoid double cysts with infection on the buttock: A case report and literature review.

RATIONALE: Epidermoid cyst (EC) is a common clinical condition and it can be filled with keratinized material. EC often represents painless, slow progressive growth, and single cyst. The cyst is usually 1 to 5 cm in size. Giant epidermoid cysts on the buttock area are extremely rare, and reports of giant epidermoid double cysts on the buttock are even rarer. PATIENT CONCERNS: This paper reports a patient with a painless mass was on the left buttock. DIAGNOSIS: A giant epidermoid double cysts with infection in a left buttock paranal location. INTERVENTIONS: The mass was surgically removed. OUTCOMES: The patient recovered well after surgical treatment and currently has no recurrence. CONCLUSION: For patients with EC, MRI is recommended as a routine examination before surgery in order to detect the variation and extent of the cyst early. This lays a foundation for the complete resection of the lesion during the operation. The review of relevant literature will hopefully be helpful to clinicians.

Optimized fuzzy K-nearest neighbor approach for accurate lung cancer prediction based on radial endobronchial ultrasonography.

Radial endobronchial ultrasonography (R-EBUS) has been a surge in the development of new ultrasonography for the diagnosis of pulmonary diseases beyond the central airway. However, it faces challenges in accurately pinpointing the location of abnormal lesions. Therefore, this study proposes an improved machine learning model aimed at distinguishing between malignant lung disease (MLD) from benign lung disease (BLD) through R-EBUS features. An enhanced manta ray foraging optimization based on elite perturbation search and cyclic mutation strategy (ECMRFO) is introduced at first. Experimental validation on 29 test functions from CEC 2017 demonstrates that ECMRFO exhibits superior optimization capabilities and robustness compared to other competing algorithms. Subsequently, it was combined with fuzzy k-nearest neighbor for the classification prediction of BLD and MLD. Experimental results indicate that the proposed modal achieves a remarkable prediction accuracy of up to 99.38%. Additionally, parameters such as R-EBUS1 Circle-dense sign, R-EBUS2 Hemi-dense sign, R-EBUS5 Onionskin sign and CCT5 mediastinum lymph node are identified as having significant clinical diagnostic value.

Genetic underpinnings explored: OPA1 deletion and complex phenotypes on chromosome 3q29.

BACKGROUND: Copy number variations (CNVs) have emerged as significant contributors to the elusive genetic causality of inherited eye diseases. In this study, we describe a case with optic atrophy and a brain aneurysm, in which a de novo CNV 3q29 deletion was identified. CASE PRESENTATION: A 40-year-old female patient was referred to our department after undergoing aneurysm transcatheter arterial embolization for a brain aneurysm. She had no history of systemic diseases, except for unsatisfactory best-corrected visual acuity (BCVA) since elementary school. Electrophysiological tests confirmed the findings in retinal images, indicating optic nerve atrophy. Chromosomal microarray analysis revealed a de novo deletion spanning 960 kb on chromosome 3q29, encompassing OPA1 and six neighboring genes. Unlike previously reported deletions in this region associated with optic atrophy, neuropsychiatric disorders, and obesity, this patient displayed a unique combination of optic atrophy and a brain aneurysm. However, there is no causal relationship between the brain aneurysm and the CNV. CONCLUSION: In conclusion, the optic atrophy is conclusively attributed to the OPA1 deletion, and the aneurysm could be a coincidental association. The report emphasizes the likelihood of underestimating OPA1 deletions due to sequencing technology limitations. Recognizing these constraints, healthcare professionals must acknowledge these limitations and consistently search for OPA1 variants/deletions in Autosomal Dominant Optic Atrophy (ADOA) patients with negative sequencing results. This strategic approach ensures a more comprehensive exploration of copy-number variations, ultimately enhancing diagnostic precision in the field of genetic disorders.

Progress in the surgical treatment of sacrococcygeal pilonidal sinus: a review.

BACKGROUND: A pilonidal sinus (PS) is an acquired disease resulting from recurrent infections and chronic inflammation. A PS involving the sacrococcyx is referred to as a sacrococcygeal PS (SPS). An SPS is a rare chronic infectious disease for which surgery is a good choice. The incidence of SPS has gradually increased worldwide in recent years. However, surgeons have not reached a consensus on the preferred surgical approach for SPS. The authors performed a systematic review and meta-analysis to analyze differences in the efficacy of different surgical approaches for the treatment of SPS. METHODS: A systematic search was conducted in the PubMed database covering the period from 1 January 2003, to 28 February 2023. The primary outcome parameters were recurrence and infection. Finally, statistical analysis (meta-analysis) was carried out using RevMan 5.4.1 software. In addition, we systematically reviewed the latest progress in the surgical treatment of SPS over the past 20 years, especially as reported in the past 3 years. RESULTS: Twenty-seven articles, 54 studies, and 3612 participants were included in this meta-analysis. The recurrence rate following the midline closure (MC) technique was much higher than that of other techniques. Among the techniques analyzed, the differences between MC and Limberg flap (LF), and between MC and marsupialization were statistically significant [ P =0.0002, risk ratio (RR)=6.15, 95% CI 2.40, 15.80; P =0.01, RR=12.70, 95% CI 1.70, 95.06]. The recurrence rate of open healing was higher than that of the Karydakis flap (KF) technique, and the difference was statistically significant ( P =0.02, RR=6.04, 95% CI 1.37, 26.55). Most of the results comparing MC with other techniques suggested that the former had a higher infection rate, and the difference between MC and LF was statistically significant ( P =0.0005, RR=4.14, 95% CI 1.86, 9.23). Comparison between KF and LF, modified LF and KF showed that the differences were not statistically significant in terms of recurrence and infection ( P ≥0.05). CONCLUSIONS: There are various surgical treatment options for SPS, including incision and drainage, excision of diseased tissue with primary closure and secondary healing, and minimally invasive surgery. It is still not possible to determine which surgical technique should be considered the gold standard for treatment, as even the results of different researchers using the same operation method are conflicting. But what is certain is that the midline closure technique has a much higher incidence of postoperative recurrence and infection than other techniques. Therefore, the anorectal surgeon should formulate the most suitable individualized plan for the patient based on a comprehensive evaluation of the patient's wishes, appearance of the SPS, and the professional ability of the surgeon.

Long non-coding RNA and Evolving drug resistance in lung cancer.

Non-small cell lung cancer (NSCLC) is one of the most devastating cancers with a high incidence and mortality rates of all cancers. Locally advanced or metastatic NSCLC patients can benefit from platinum-based chemotherapy and targeted therapy drugs. Nevertheless, primary or acquired drug resistance will result in ineffective treatment, leading to tumor progression. The detailed mechanism underlying drug resistance to NSCLC are complicated and result from various factor. Among them, long noncoding RNAs (lncRNAs) have been found to be critically involved in NSCLC development and play a vital role in mediating therapy resistance. In this review, we attempt to systematically summarize the mechanisms underlying the lncRNA-mediated resistance to chemotherapy agents and targeted therapy drugs against lung cancer.

Identification of Pulmonary Hypertension Animal Models Using a New Evolutionary Machine Learning Framework Based on Blood Routine Indicators.

Pulmonary Hypertension (PH) is a global health problem that affects about 1% of the global population. Animal models of PH play a vital role in unraveling the pathophysiological mechanisms of the disease. The present study proposes a Kernel Extreme Learning Machine (KELM) model based on an improved Whale Optimization Algorithm (WOA) for predicting PH mouse models. The experimental results showed that the selected blood indicators, including Haemoglobin (HGB), Hematocrit (HCT), Mean, Platelet Volume (MPV), Platelet distribution width (PDW), and Platelet-Large Cell Ratio (P-LCR), were essential for identifying PH mouse models using the feature selection method proposed in this paper. Remarkably, the method achieved 100.0% accuracy and 100.0% specificity in classification, demonstrating that our method has great potential to be used for evaluating and identifying mouse PH models.

Multiphase holdup measurement of oil-gas-water flow using new dual receiver fiber-optical probe array multiphase logging tool.

To solve the problem of multiphase holdup measurement, a new dual-receiver fiber-optical probe array multiphase logging tool (NDRFOPA_MLT) is designed and developed. This paper first constructed the mechanism model of an NDRFOP for phase holdup measurement by using the ray tracing method and theoretically analyzed the feasibility of NDRFOP to measure phase holdup; considering the shortcomings of NDRFOP local measurement, a NDRFOPA sensor for oil production three-phase flow is designed and developed. At the same time, the volume of fluid model was used to simulate the distribution characteristics of the medium in the NDRFOPA_MLT measurement pipeline under the working conditions of oil-gas-water flow with a total flow rate range of 0.42-1.25 m3/h, water holdup range of 50%-80%, oil holdup range of 10%-30%, and gas holdup range of 10%-40%. In addition, the NDRFOPA_MLT measurement models for different multiphase flow conditions were established by the ZEMAX ray tracing method, and the sensitivity distribution, response characteristics, and phase holdup measurement methods were studied to obtain the phase holdup measurement results under multiphase flow conditions. Finally, a multiphase flow experimental platform with a measurement pipe diameter of 20 mm and a measurement pipe length of 300 mm was established, and experiments were conducted under multiphase flow conditions, such as a gas flow rate range of 0.04-0.16 m3/h, oil flow rate range of 0.64-1.70 m3/h, and water flow rate range of 0.53-2.58 m3/h. The experimental results showed that phase holdup measurement error was mainly kept within 10%.

An optimized machine learning method for predicting wogonin therapy for the treatment of pulmonary hypertension.

Human health is at risk from pulmonary hypertension (PH), characterized by decreased pulmonary vascular resistance and constriction of the pulmonary vessels, resulting in right heart failure and dysfunction. Thus, preventing PH and monitoring its progression before treating it is vital. Wogonin, derived from the leaves of Scutellaria baicalensis Georgi, exhibits remarkable pharmacological activity. In this study, we examined the effectiveness of wogonin in mitigating the progression of PH in mice using right heart catheterization and hematoxylin-eosin (HE) staining. As an alternative to minimize the possibility of harming small animals, we present a scientifically effective feature selection method (BSCDWOA-KELM) that will allow us to develop a novel simpler noninvasive prediction method for wogonin in treating PH. In this method, we use the proposed enhanced whale optimizer (SCDWOA) in conjunction with the kernel extreme learning machine (KELM). Initially, we let SCDWOA perform global optimization experiments on the IEEE CEC2014 benchmark function set to verify its core advantages. Lastly, 12 public and PH datasets are examined for feature selection experiments using BSCDWOA-KELM. As shown in the experimental results for global optimization, the proposed SCDWOA has better convergence performance. Meanwhile, the proposed binary SCDWOA (BSCDWOA) significantly improves the ability of KELM to classify data. By utilizing the BSCDWOA-KELM, key indicators such as the Red blood cell (RBC), the Haemoglobin (HGB), the Lymphocyte percentage (LYM%), the Hematocrit (HCT), and the Red blood cell distribution width-size distribution (RDW-SD) can be efficiently screened in the Pulmonary hypertension dataset, and one of its most essential points is its accuracy of greater than 0.98. Consequently, the BSCDWOA-KELM introduced in this study can be used to predict wogonin therapy for treating pulmonary hypertension in a simple and noninvasive manner.

The Value of Electroretinography in Identifying Candidate Genes for Inherited Retinal Dystrophies: A Diagnostic Guide.

Inherited retinal dystrophies (IRDs) are a group of heterogeneous diseases caused by genetic mutations that specifically affect the function of the rod, cone, or bipolar cells in the retina. Electroretinography (ERG) is a diagnostic tool that measures the electrical activity of the retina in response to light stimuli, and it can help to determine the function of these cells. A normal ERG response consists of two waves, the a-wave and the b-wave, which reflect the activity of the photoreceptor cells and the bipolar and Muller cells, respectively. Despite the growing availability of next-generation sequencing (NGS) technology, identifying the precise genetic mutation causing an IRD can be challenging and costly. However, certain types of IRDs present with unique ERG features that can help guide genetic testing. By combining these ERG findings with other clinical information, such as on family history and retinal imaging, physicians can effectively narrow down the list of candidate genes to be sequenced, thereby reducing the cost of genetic testing. This review article focuses on certain types of IRDs with unique ERG features. We will discuss the pathophysiology and clinical presentation of, and ERG findings on, these disorders, emphasizing the unique role ERG plays in their diagnosis and genetic testing.

Clinical Characteristics and Genetic Variants in Taiwanese Patients With PROM1-Related Inherited Retinal Disorders.

Purpose: This study investigated the clinical characteristics of patients with PROM1-related inherited retinal diseases (IRDs). Methods: Patients diagnosed with IRDs who had mutations in PROM1 were identified at Linkou Chang Gung Memorial Hospital and Kaohsiung Medical University Hospital in Taiwan. Information on clinical characteristics and best-corrected visual acuity was recorded. Color fundus (CF) images, fundus autofluorescence photography (FAF), spectral-domain optical coherence tomography (SD-OCT), and electroretinograms (ERGs) were analyzed to examine patient phenotypes. PROM1 variants were detected using whole exome sequencing and verified by Sanger sequencing. Results: Fourteen patients from nine families with PROM1-related IRDs were analyzed. Most patients exhibited chorioretinal atrophy in the macular area, with or without extramacular involvement on CF. Similarly, hypo-autofluorescence confined to the macular area, with or without extramacular involvement, was present for most patients on FAF. Furthermore, SD-OCT revealed outer retinal tubulations and focal or diffuse retinal thinning. ERGs showed variable findings, including maculopathy with normal ERG, subnormal cone response, and extinguished rod and cone responses. We detected five variants of the PROM1 gene, including c.139del, c.794del, c.1238T>A, c.2110C>T, and c.1117C>T. Conclusions: In this study, we evaluated 14 Taiwanese patients with five PROM1 variants. Additionally, incomplete penetrance of heterozygous PROM1 variants was observed. Furthermore, patients with autosomal dominant PROM1 variants had lesions in the macular area and the peripheral region of the retina. SD-OCT serves as a useful tool for early detection of PROM1-related IRDs, as it captures certain signs of such diseases.

An evolutionary machine learning for pulmonary hypertension animal model from arterial blood gas analysis.

Pulmonary hypertension (PH) is a rare and fatal condition that leads to right heart failure and death. The pathophysiology of PH and potential therapeutic approaches are yet unknown. PH animal models' development and proper evaluation are critical to PH research. This work presents an effective analysis technology for PH from arterial blood gas analysis utilizing an evolutionary kernel extreme learning machine with multiple strategies integrated slime mould algorithm (MSSMA). In MSSMA, two efficient bee-foraging learning operators are added to the original slime mould algorithm, ensuring a suitable trade-off between intensity and diversity. The proposed MSSMA is evaluated on thirty IEEE benchmarks and the statistical results show that the search performance of the MSSMA is significantly improved. The MSSMA is utilised to develop a kernel extreme learning machine (MSSMA-KELM) on PH from arterial blood gas analysis. Comprehensively, the proposed MSSMA-KELM can be used as an effective analysis technology for PH from arterial Blood gas analysis with an accuracy of 93.31%, Matthews coefficient of 90.13%, Sensitivity of 91.12%, and Specificity of 90.73%. MSSMA-KELM can be treated as an effective approach for evaluating mouse PH models.

Detection of COVID-19 severity using blood gas analysis parameters and Harris hawks optimized extreme learning machine.

Coronavirus disease-2019 (COVID-19) has made the world more cautious about widespread viruses, and a tragic pandemic that was caused by a novel coronavirus has harmed human beings in recent years. The new coronavirus pneumonia outbreak is spreading rapidly worldwide. We collect arterial blood samples from 51 patients with a COVID-19 diagnosis. Blood gas analysis is performed using a Siemens RAPID Point 500 blood gas analyzer. To accurately determine the factors that play a decisive role in the early recognition and discrimination of COVID-19 severity, a prediction framework that is based on an improved binary Harris hawk optimization (HHO) algorithm in combination with a kernel extreme learning machine is proposed in this paper. This method uses specular reflection learning to improve the original HHO algorithm and is referred to as HHOSRL. The experimental results show that the selected indicators, such as age, partial pressure of oxygen, oxygen saturation, sodium ion concentration, and lactic acid, are essential for the early accurate assessment of COVID-19 severity by the proposed feature selection method. The simulation results show that the established methodlogy can achieve promising performance. We believe that our proposed model provides an effective strategy for accurate early assessment of COVID-19 and distinguishing disease severity. The codes of HHO will be updated in https://aliasgharheidari.com/HHO.html.