Radiomics in breast cancer: Current advances and future directions.

Breast cancer is a common disease that causes great health concerns to women worldwide. During the diagnosis and treatment of breast cancer, medical imaging plays an essential role, but its interpretation relies on radiologists or clinical doctors. Radiomics can extract high-throughput quantitative imaging features from images of various modalities via traditional machine learning or deep learning methods following a series of standard processes. Hopefully, radiomic models may aid various processes in clinical practice. In this review, we summarize the current utilization of radiomics for predicting clinicopathological indices and clinical outcomes. We also focus on radio-multi-omics studies that bridge the gap between phenotypic and microscopic scale information. Acknowledging the deficiencies that currently hinder the clinical adoption of radiomic models, we discuss the underlying causes of this situation and propose future directions for advancing radiomics in breast cancer research.

Impact of Interprofessional Collaborative Practice on Functional Improvements Among Post-Acute Stroke Survivors: A Retrospective Cross-Sectional Study.

Background: Stroke survivors in post-acute care frequently experience physiological dysfunction and reduced quality of life. This study aims to assess the impact of the Post-Acute Care Interprofessional Collaborative Practice (PAC-IPCP) program across different care settings, and to identify sensitive tools for assessing physiological functions among post-acute stroke survivors. Methods: This retrospective study involved 210 stroke survivors in Taiwan. Participants who self-selection for their preferred between hospital care setting and home care setting under PAC-IPCP. Multiple assessment tools were utilized, including the Barthel Index (BI), Functional Oral Intake Scale (FOIS), Mini Nutritional Assessment (MNA), EQ-5D-3L, and Instrumental Activities of Daily Living (IADL). The logistic regression was used to estimate the odds ratios of various functional assessment tools between hospital and home care settings. Additionally, the area under the ROC curves was used to determine which functional assessment tools had higher accuracy in measuring the association between care settings. Results: Of the study population, 138 stroke survivors (65.71%) selection hospital care setting and 72 stroke survivors (34.29%) selection home care setting. The PAC-IPCP program was equally effective in both care settings for physical function status and quality of life improvements. Specifically, the BI emerged as the most sensitive tool for assessing care settings, with an adjusted OR of 1.04 (95% CI:1.02-1.07, p < 0.0001; AUC = 0.7557). IPCP-based hospital and home care models are equally effective in facilitating improved functional outcomes in post-acute stroke survivors. Conclusion: The PAC-IPCP program is versatile and effective across care settings. The BI stands out as a robust assessment tool for physiological functions, endorsing its broader clinical application. Future studies should also consider swallowing and nutritional status for a more holistic approach to rehabilitation.

Inhibition of 5-HT alleviates PTSD-like behaviors and promotes hippocampal neuroplasticity by modulating hippocampal autophagy in rats.

5-Hydroxytryptamine (5-HT) plays a substantial role in mitigating depression and anxiety. However, the potential effects of 5-HT against posttraumatic stress disorder (PTSD) and its underlying mechanisms remain unclear. Elevated plus maze test evaluates anxiety-related behaviors, and the open field test is used to assess overall activity levels and anxiety. Inflammatory cytokine levels were determined using ELISA. The levels of 5-HT and dopamine were measured using HPLC. mRNA and protein levels were examined by PCR and Western blot, respectively. Rats exposed to single prolonged stress (SPS) exhibited typical PTSD-like phenotypes, with decreased levels of 5-HT in the hippocampus and significant reductions in its downstream targets, brain-derived neurotrophic factor (BDNF) and TrkB. In addition, it was discovered that the autophagy signaling pathway might be involved in regulating hippocampal BDNF in rats exposed to SPS. Subsequent treatment with an intracerebral injection of sh-SERT significantly inhibited anxiety and cognitive dysfunction in rats. Moreover, sh-SERT treatment was observed to substantially reverse the increase in autophagy signaling protein expression and consequently improve the expression of BDNF and TrkB proteins, which had been reduced. The current study demonstrates that sh-SERT exhibits significant anti-PTSD effects, potentially mediated in part through the reduction of cellular autophagy to enhance hippocampal synaptic plasticity.NEW & NOTEWORTHY The study demonstrated that sh-SERT exhibits significant anti-posttraumatic stress disorder (PTSD) effects, potentially mediated in part through the reduction of cellular autophagy to enhance hippocampal synaptic plasticity.

Transcription factor TaNF-YB2 interacts with partners TaNF-YA7/YC7 and transcriptionally activates distinct stress-defensive genes to modulate drought tolerance in T. Aestivum.

BACKGROUND: Drought stress limits significantly the crop productivity. However, plants have evolved various strategies to cope with the drought conditions by adopting complex molecular, biochemical, and physiological mechanisms. Members of the nuclear factor Y (NF-Y) transcription factor (TF) family constitute one of the largest TF classes and are involved in plant responses to abiotic stresses. RESULTS: TaNF-YB2, a NY-YB subfamily gene in T. aestivum, was characterized in this study focusing on its role in mediating plant adaptation to drought stress. Yeast two-hybrid (Y-2 H), biomolecular fluoresence complementation (BiFC), and Co-immunoprecipitation (Co-IP) assays indicated that TaNF-YB2 interacts with the NF-YA member TaNF-YA7 and NF-YC family member TaNF-YC7, which constitutes a heterotrimer TaNF-YB2/TaNF-YA7/TaNF-YC7. The TaNF-YB2 transcripts are induced in roots and aerial tissues upon drought signaling; GUS histochemical staining analysis demonstrated the roles of cis-regulatory elements ABRE and MYB situated in TaNF-YB2 promoter to contribute to target gene response to drought. Transgene analysis on TaNF-YB2 confirmed its functions in regulating drought adaptation via modulating stomata movement, osmolyte biosynthesis, and reactive oxygen species (ROS) homeostasis. TaNF-YB2 possessed the abilities in transcriptionally activating TaP5CS2, the P5CS family gene involving proline biosynthesis and TaSOD1, TaCAT5, and TaPOD5, the genes encoding antioxidant enzymes. Positive correlations were found between yield and the TaNF-YB2 transcripts in a core panel constituting 45 wheat cultivars under drought condition, in which two types of major haplotypes including TaNF-YB2-Hap1 and -Hap2 were included, with the former conferring more TaNF-YB2 transcripts and stronger plant drought tolerance. CONCLUSIONS: TaNF-YB2 is transcriptional response to drought stress. It is an essential regulator in mediating plant drought adaptation by modulating the physiological processes associated with stomatal movement, osmolyte biosynthesis, and reactive oxygen species (ROS) homeostasis, depending on its role in transcriptionally regulating stress response genes. Our research deepens the understanding of plant drought stress underlying NF-Y TF family and provides gene resource in efforts for molecular breeding the drought-tolerant cultivars in T. aestivum.

Health-related quality of life by veterans RAND 12 and healthcare resource utilization in cancer patients with sleep disorders: insights from the Medical Expenditure Panel Survey.

PURPOSE: This study aims to investigate the joint effects of cancer and sleep disorders on the health-related quality of life (HRQoL), healthcare resource utilization, and expenditures among US adults. METHODS: Utilizing the 2018-2019 Medical Expenditure Panel Survey (MEPS) database, a sample of 25,274 participants was categorized into four groups based on cancer and sleep disorder status. HRQoL was assessed using the VR-12 questionnaire. Generalized linear model (GLM) with a log-linear regression model combined gamma distribution was applied for the analysis of healthcare expenditure data. RESULTS: Individuals with both cancer and sleep disorders (C+/S+) exhibited notably lower physical health (PCS) and mental health (MCS) scores-1.45 and 1.87 points lower, respectively. They also showed significantly increased clinic visits (2.12 times), outpatient visits (3.59 times), emergency visits (1.69 times), and total medical expenditures (2.08 times) compared to those without cancer or sleep disorders (C-/S-). In contrast, individuals with sleep disorders alone (C-/S+) had the highest number of prescription drug usage (2.26 times) and home health care days (1.76 times) compared to the reference group (C-/S-). CONCLUSIONS: Regardless of cancer presence, individuals with sleep disorders consistently reported compromised HRQoL. Furthermore, those with cancer and sleep disorders experienced heightened healthcare resource utilization, underscoring the considerable impact of sleep disorders on overall quality of life. IMPLICATIONS FOR CANCER SURVIVORS: The findings of this study address the importance of sleep disorders among cancer patients and their potential implications for cancer care. Healthcare professionals should prioritize screening, education, and tailored interventions to support sleep health in this population.

Characteristics of "do not resuscitate" orders among elderly patients receiving mechanical ventilation in the intensive care unit in Taiwan.

Objective: As patient life expectancy has increased and people are living longer than before, the rate of mechanical ventilation among elderly patients in the intensive care unit has increased. Older patients who receive mechanical ventilation and have multiple comorbidities are more likely to have a do not resuscitate order than are younger patients with fewer comorbidities. The aim of our study was to describe the patient characteristics and predictive factors of do not resuscitate orders during hospitalization among elderly patients who received ventilation in the intensive care unit. Methods: This was a retrospective review of the electronic medical records of patients in the intensive care unit of a teaching hospital in southern Taiwan. We enrolled patients admitted to the general intensive care unit from January 1, 2018, to September 31, 2020, and patients older than 80 years who experienced respiratory failure, were intubated and received mechanical ventilation. We analyzed patient demographics, disease severity during hospitalization and comorbidities. If a patient had multiple admissions to the intensive care unit, only the first admission was recorded. Results: Of the 305 patients over 80 years of age with respiratory failure who were intubated and placed on a ventilator, 66 were excluded because of incomplete data, and 13 were excluded because they had already signed a do not resuscitate order prior to admission to the hospital. Ultimately, 226 patients were included in this study. A higher acute physiology and chronic health evaluation II score (>30) was also associated with an increased likelihood of a do not resuscitate order (odds ratio (OR) = 3.85, 95% CI = 1.09-13.62, p = 0.0362). Patients who had acute kidney injury or cerebrovascular accident were more likely to have a do not resuscitate order (OR = 2.74, 95% CI = 1.03-7.28, p = 0.0428 and OR = 7.32, 95% CI = 2.02-26.49, p = 0.0024, respectively). Conclusion: Our study showed that older age, greater disease severity, and certain critical interventions were associated with a greater propensity for do not resuscitate orders, which is crucial for understanding patient preferences and guiding end-of-life care discussions. These findings highlight the importance of clinical severity and specific health events in predicting end-of-life care preferences in older patient groups.

Optimizing the image quality of peripancreatic blood vessels through the clinical application of single-energy spectral computed tomography (CT) imaging.

Background: With the increase of pancreatic tumor patients in recent years, there is an urgent need to find a way to treat pancreatic tumors. Surgery is one of the best methods for the treatment of pancreatic tumors, the success of which depends on the evaluation of peripancreatic vessels before surgery. Computed tomography (CT), as a non-invasive, fast, and economical auxiliary examination method, is undoubtedly one of the best means of clinical auxiliary examination. In this study, we investigated the impact of single-energy spectral CT imaging on the image quality of peripancreatic blood vessels and the clinical value of low-keV imaging in enhancing the image quality of peripancreatic arteriovenous vessels. Methods: We prospectively enrolled 103 patients who underwent abdominal vascular-enhanced CT examinations at the Affiliated Hospital of Hebei University between December 2022 and May 2023 and who were all scanned with the dual-energy feature on the United Imaging ATLAS scanner. The images were reconstructed at 70 keV, mixed energy, and optimized single energy in the post-processing station of United Imaging Healthcare Technology Co., Ltd. The CT value and contrast-to-noise ratio (CNR) of the superior mesenteric artery (SMA), gastroduodenal artery (GDA), inferior pancreaticoduodenal artery (IPDA), and superior mesenteric vein (SMV) were compared across energy levels, and then the image quality was subjectively evaluated. One-way analysis of variance and rank-sum tests were utilized for the statistical analysis. Results: The CT values of SMA, GDA, IPDA, and SMV in the optimal single energy group were 358.37±70.24, 323.36±88.23, 300.76±76.27, and 257.74±20.56 Hounsfield unit (HU), respectively, which were superior to those in the mixed energy (241.66±47.69, 235.17±53.71, 207.36±45.17, and 187.39±23.21 HU) and 70 keV groups (260.89±54.27, 252.41±58.87, 223.17±43.65, and 203.18±18.17 HU) (P<0.05). The diagnostic efficacy was greater in the optimal single energy group than in the other 2 groups (4.63±0.50, 3.91±0.57, and 4.23±0.83) (P<0.05). Conclusions: The optimal single energy for showing peripancreatic blood vessels is 62±7 keV when utilizing single-energy spectral CT imaging.

Discovery and functional investigation of BMP4 as a new causative gene for human congenital heart disease.

OBJECTIVE: Aggregating evidence highlights the strong genetic basis underpinning congenital heart disease (CHD). Here BMP4 was chosen as a prime candidate gene causative of human CHD predominantly because BMP4 was amply expressed in the embryonic hearts and knockout of Bmp4 in mice led to embryonic demise mainly from multiple cardiovascular developmental malformations. The aim of this retrospective investigation was to discover a novel BMP4 mutation underlying human CHD and explore its functional impact. METHODS: A sequencing examination of BMP4 was implemented in 212 index patients suffering from CHD and 236 unrelated non-CHD individuals as well as the family members available from the proband carrying a discovered BMP4 mutation. The impacts of the discovered CHD-causing mutation on the expression of NKX2-5 and TBX20 induced by BMP4 were measured by employing a dual-luciferase analysis system. RESULTS: A new heterozygous BMP4 mutation, NM_001202.6:c.318T>G;p.(Tyr106*), was found in a female proband affected with familial CHD. Genetic research of the mutation carrier's relatives unveiled that the truncating mutation was in co-segregation with CHD in the pedigree. The nonsense mutation was absent from 236 unrelated non-CHD control persons. Quantitative biologic measurement revealed that Tyr106*-mutant BMP4 failed to induce the expression of NKX2-5 and TBX20, two genes whose expression is lost in CHD. CONCLUSION: The current findings indicate BMP4 as a new gene predisposing to human CHD, allowing for improved prenatal genetic counseling along with personalized treatment of CHD patients.

Application and progress of artificial intelligence technology in the segmentation of hyperreflective foci in OCT images for ophthalmic disease research.

With the advancement of retinal imaging, hyperreflective foci (HRF) on optical coherence tomography (OCT) images have gained significant attention as potential biological biomarkers for retinal neuroinflammation. However, these biomarkers, represented by HRF, present pose challenges in terms of localization, quantification, and require substantial time and resources. In recent years, the progress and utilization of artificial intelligence (AI) have provided powerful tools for the analysis of biological markers. AI technology enables use machine learning (ML), deep learning (DL) and other technologies to precise characterization of changes in biological biomarkers during disease progression and facilitates quantitative assessments. Based on ophthalmic images, AI has significant implications for early screening, diagnostic grading, treatment efficacy evaluation, treatment recommendations, and prognosis development in common ophthalmic diseases. Moreover, it will help reduce the reliance of the healthcare system on human labor, which has the potential to simplify and expedite clinical trials, enhance the reliability and professionalism of disease management, and improve the prediction of adverse events. This article offers a comprehensive review of the application of AI in combination with HRF on OCT images in ophthalmic diseases including age-related macular degeneration (AMD), diabetic macular edema (DME), retinal vein occlusion (RVO) and other retinal diseases and presents prospects for their utilization.

Shock index to predict outcomes in patients with trauma following traffic collisions: a retrospective cohort study.

PURPOSE: Taiwan, which has a rate of high vehicle ownership, faces significant challenges in managing trauma caused by traffic collisions. In Taiwan, traffic collisions contribute significantly to morbidity and mortality, with a high incidence of severe bleeding trauma. The shock index (SI) and the modified shock index (MSI) have been proposed as early indicators of hemodynamic instability. In this study, we aimed to assess the efficacy of SI and MSI in predicting adverse outcomes in patients with trauma following traffic collisions. METHODS: This retrospective cohort study was conducted at Chi Mei Hospital from January 2015 to December 2020. The comprehensive analysis included 662 patients, with data collected on vital signs and outcomes such as mortality, blood transfusion, emergent surgical intervention (ESI), transarterial embolization (TAE), and intensive care unit (ICU) admission. Optimal cutoff points for SI and MSI were identified by calculating the Youden index. Logistic regression analysis was used to assess outcomes, adjusting for demographic and injury severity variables. RESULTS: An SI threshold of 1.11 was associated with an increased risk of mortality, while an SI of 0.84 predicted the need for blood transfusion in the context of traffic collisions. Both SI and MSI demonstrated high predictive power for mortality and blood transfusion, with acceptable accuracy for TAE, ESI, and ICU admission. Logistic regression analyses confirmed the independence of SI and MSI as risk factors for adverse outcomes, thus, providing valuable insights into their clinical utility. CONCLUSIONS: SI and MSI are valuable tools for predicting mortality and blood transfusion needs in patients with trauma due to traffic collisions. These findings advance the quality of care for patients with trauma during their transition from the emergency room to the ICU, facilitating prompt and reliable decision-making processes and improving the care of patients with trauma.

Comparison of Machine Learning Models Using Diffusion-Weighted Images for Pathological Grade of Intrahepatic Mass-Forming Cholangiocarcinoma.

Is the radiomic approach, utilizing diffusion-weighted imaging (DWI), capable of predicting the various pathological grades of intrahepatic mass-forming cholangiocarcinoma (IMCC)? Furthermore, which model demonstrates superior performance among the diverse algorithms currently available? The objective of our study is to develop DWI radiomic models based on different machine learning algorithms and identify the optimal prediction model. We undertook a retrospective analysis of the DWI data of 77 patients with IMCC confirmed by pathological testing. Fifty-seven patients initially included in the study were randomly assigned to either the training set or the validation set in a ratio of 7:3. We established four different classifier models, namely random forest (RF), support vector machines (SVM), logistic regression (LR), and gradient boosting decision tree (GBDT), by manually contouring the region of interest and extracting prominent radiomic features. An external validation of the model was performed with the DWI data of 20 patients with IMCC who were subsequently included in the study. The area under the receiver operating curve (AUC), accuracy (ACC), precision (PRE), sensitivity (REC), and F1 score were used to evaluate the diagnostic performance of the model. Following the process of feature selection, a total of nine features were retained, with skewness being the most crucial radiomic feature demonstrating the highest diagnostic performance, followed by Gray Level Co-occurrence Matrix lmc1 (glcm-lmc1) and kurtosis, whose diagnostic performances were slightly inferior to skewness. Skewness and kurtosis showed a negative correlation with the pathological grading of IMCC, while glcm-lmc1 exhibited a positive correlation with the IMCC pathological grade. Compared with the other three models, the SVM radiomic model had the best diagnostic performance with an AUC of 0.957, an accuracy of 88.2%, a sensitivity of 85.7%, a precision of 85.7%, and an F1 score of 85.7% in the training set, as well as an AUC of 0.829, an accuracy of 76.5%, a sensitivity of 71.4%, a precision of 71.4%, and an F1 score of 71.4% in the external validation set. The DWI-based radiomic model proved to be efficacious in predicting the pathological grade of IMCC. The model with the SVM classifier algorithm had the best prediction efficiency and robustness. Consequently, this SVM-based model can be further explored as an option for a non-invasive preoperative prediction method in clinical practice.

Effects of dietary intervention on human diseases: molecular mechanisms and therapeutic potential.

Diet, serving as a vital source of nutrients, exerts a profound influence on human health and disease progression. Recently, dietary interventions have emerged as promising adjunctive treatment strategies not only for cancer but also for neurodegenerative diseases, autoimmune diseases, cardiovascular diseases, and metabolic disorders. These interventions have demonstrated substantial potential in modulating metabolism, disease trajectory, and therapeutic responses. Metabolic reprogramming is a hallmark of malignant progression, and a deeper understanding of this phenomenon in tumors and its effects on immune regulation is a significant challenge that impedes cancer eradication. Dietary intake, as a key environmental factor, can influence tumor metabolism. Emerging evidence indicates that dietary interventions might affect the nutrient availability in tumors, thereby increasing the efficacy of cancer treatments. However, the intricate interplay between dietary interventions and the pathogenesis of cancer and other diseases is complex. Despite encouraging results, the mechanisms underlying diet-based therapeutic strategies remain largely unexplored, often resulting in underutilization in disease management. In this review, we aim to illuminate the potential effects of various dietary interventions, including calorie restriction, fasting-mimicking diet, ketogenic diet, protein restriction diet, high-salt diet, high-fat diet, and high-fiber diet, on cancer and the aforementioned diseases. We explore the multifaceted impacts of these dietary interventions, encompassing their immunomodulatory effects, other biological impacts, and underlying molecular mechanisms. This review offers valuable insights into the potential application of these dietary interventions as adjunctive therapies in disease management.

Angiotensin-converting enzyme 2 alleviates liver fibrosis through the renin-angiotensin system.

The present letter to the editor is related to the study titled 'Angiotensin-converting enzyme 2 improves liver fibrosis in mice by regulating autophagy of hepatic stellate cells'. Angiotensin-converting enzyme 2 can alleviate liver fibrosis by regulating autophagy of hepatic stellate cells and affecting the renin-angiotensin system.

Neuroinflammatory imaging markers in white matter: insights into the cerebral consequences of post-acute sequelae of COVID-19 (PASC).

Symptoms of coronavirus disease 2019 (COVID-19) can persist for months or years after infection, a condition called Post-Acute Sequelae of COVID-19 (PASC). Whole-brain white matter and cortical gray matter health were assessed using multi-shell diffusion tensor imaging. Correlational tractography was utilized to dissect the nature and extent of white matter changes. In this study of 42 male essential workers, the most common symptoms of Neurological PASC (n = 24) included fatigue (n = 19) and headache (n = 17). Participants with neurological PASC demonstrated alterations to whole-brain white matter health when compared to controls made up of uninfected, asymptomatic, or mildly infected controls (n = 18). Large differences were evident between PASC and controls in measures of fractional anisotropy (Cohen's D=-0.54, P = 0.001) and cortical isotropic diffusion (Cohen's D = 0.50, P = 0.002). Symptoms were associated with white matter fractional anisotropy (fatigue: rho = -0.62, P< 0.001; headache: rho = -0.66, P < 0.001), as well as nine other measures of white and gray matter health. Brain fog was associated with improved cerebral functioning including improved white matter isotropic diffusion and quantitative anisotropy. This study identified changes across measures of white and gray matter connectivity, neuroinflammation, and cerebral atrophy that were interrelated and associated with differences in symptoms of PASC. These results provide insights into the long-term cerebral implications of COVID-19.

Discovery of BMP10 as a new gene underpinning congenital heart defects.

OBJECTIVE: Aggregating evidence convincingly establishes the predominant genetic basis underlying congenital heart defects (CHD), though the heritable determinants contributing to CHD in the majority of cases remain elusive. In the current investigation, BMP10 was selected as a prime candidate gene for human CHD mainly due to cardiovascular developmental abnormalities in Bmp10-knockout animals. The objective of this retrospective study was to identify a new BMP10 mutation responsible for CHD and characterize the functional effect of the identified CHD-causing BMP10 mutation. METHODS: Sequencing assay of BMP10 was fulfilled in a cohort of 276 probands with various CHD and a total of 288 non-CHD volunteers. The available family members from the proband harboring an identified BMP10 mutation were also BMP10-genotyped. The effect of the identified CHD-causative BMP10 mutation on the transactivation of TBX20 and NKX2.5 by BMP10 was quantitatively analyzed in maintained HeLa cells utilizing a dual-luciferase reporter assay system. RESULTS: A novel heterozygous BMP10 mutation, NM_014482.3:c.247G>T;p.(Glu83*), was identified in one proband with patent ductus arteriosus (PDA), which was confirmed to co-segregate with the PDA phenotype in the mutation carrier's family. The nonsense mutation was not observed in 288 non-CHD volunteers. Functional analysis unveiled that Glu83*-mutant BMP10 had no transactivation on its two representative target genes TBX20 and NKX2.5, which were both reported to cause CHD. CONCLUSION: These findings provide strong evidence indicating that genetically compromised BMP10 predisposes human beings to CHD, which sheds light on the new molecular mechanism that underlies CHD and allows for antenatal genetic counseling and individualized precise management of CHD.

Evaluation of combination of ALA-PDT and interferon for cervical low-grade squamous intraepithelial lesion (LSIL).

BACKGROUND: Cervical LSIL is a precancerous disease which requires regular follow-up. High risk patients need active interventions. Interferon and topical PDT have been used in the treatment of cervical LSIL. The aim of this study was to evaluate the combination use of topical PDT and interferon in the treatment of cervical LSIL. MATERIALS AND METHODS: A prospective study was carried out involving 159 women with cervical LSIL and high risk human papillomaviruses (hr-HPV) infection. Patients were divided into three groups. Group 1-receiving interferon suppository only, Group 2-receiving 19 mg/cm2 ALA plus post PDT interferon, and Group 3-receiving 38 mg/cm2 ALA plus post PDT interferon. The primary endpoint was pathological regression. The secondary endpoints were the HPV negative conversion rate and the adverse effects of treatment. RESULTS: At 6-12 months after PDT, for Group 1, the effective rate, CR rate and HPV negative conversion rate was 48.3 %, 43.3 % and 24.0 %, respectively. For Group 2, the effective rate, CR rate and HPV negative conversion rate were 89.3 %, 71.4 %, and 72.4 %, respectively. For Group 3, the effective rate, CR rate and HPV negative conversion rate were 91.5 %, 66.1 %, and 64.4 %, respectively, significantly higher than those of interferon only group. Two ALA dose group study showed similar efficacy. No patient experienced serious adverse effects. CONCLUSIONS: ALA-PDT combined with interferon therapy was feasible and tolerable. Two ALA dose groups showed similar outcomes in treating cervical LSIL.

TGF-ß1 Mediates the EndoMt in High Glucose-Treated Human Retinal Microvascular Endothelial Cells.

The purpose of our study was to investigate the role of TGF-ß1 in the endothelial-to-mesenchymal transition (EndoMT) and fibrosis in high glucose (HG)-treated human retinal microvascular endothelial cells (HRMECs). HRMECs were cultured not only under normal glucose (NG) conditions with or without TGF-ß1, but also under HG conditions with or without the TGF-ß1 inhibitor SB431542. The expression of TGF-ß1 was detected by real time-PCR and enzyme-linked immunosorbent assay. Morphological changes and migration of the HRMECs were observed using electron microscopy and scratch-wound assay. Endothelial markers, such as CD31 and vascular endothelial (VE)-cadherin, and the acquisition of fibrotic markers, such as alpha smooth muscle actin (α-SMA) and fibroblast-specific protein-1 (FSP-1), were determined by immunofluorescent staining and western blot. The level of TGF-ß1 was significantly upregulated in HG-treated HRMECs. And HG stimulation promoted obvious morphological changes and the migration ability in HRMECs. Our results also demonstrated increased expression of α-SMA and FSP-1, and decreased expression of CD31 and VE-cadherin, in HG-treated HRMECs. These EndoMT-related changes were promoted by TGF-ß1 and abrogated by SB431542. The results of this study demonstrated the important role of TGF-ß1 in HG-induced vitreoretinal fibrosis. EndoMT is likely to be involved in the associated effects.

Somatic GATA4 mutation contributes to tetralogy of Fallot.

Tetralogy of Fallot (TOF) is the most prevalent cyanotic congenital heart pathology and causes infant morbidity and mortality worldwide. GATA-binding protein 4 (GATA4) serves as a pivotal transcriptional factor for embryonic cardiogenesis and germline GATA4 mutations are causally linked to TOF. However, the effects of somatic GATA4 mutations on the pathogenesis of TOF remain to be ascertained. In the present study, sequencing assay of GATA4 was performed utilizing genomic DNA derived from resected heart tissue specimens as well as matched peripheral blood specimens of 62 patients with non-familial TOF who underwent surgical treatment for TOF. Sequencing of GATA4 was also performed using the heart tissue specimens as well as matched peripheral venous blood samples of 68 sporadic cases who underwent heart valve displacement because of rheumatic heart disorder and the peripheral venous whole blood samples of 216 healthy subjects. The function of the mutant was explored by dual-luciferase activity analysis. Consequently, a new GATA4 mutation, NM_002052.5:c.708T>G;p.(Tyr236*), was found in the heart tissue of one patient with TOF. No mutation was detected in the heart tissue of the 68 cases suffering from rheumatic heart disorder or in the venous blood samples of all 346 individuals. GATA4 mutant failed to transactivate its target gene, myosin heavy chain 6. Additionally, this mutation nullified the synergistic transactivation between GATA4 and T-box transcription factor 5 or NK2 homeobox 5, two genes causative for TOF. Somatic GATA4 mutation predisposes TOF, highlighting the significant contribution of somatic variations to the molecular pathogenesis underpinning TOF.

Functional characterization of RIP2 in large yellow croaker (Larimichthys crocea), a protein involved in the host antiviral responses via NF-κΒ, IRF3/7 related signaling.

As an adaptor protein functions essentially in the activation of NF-κΒ and MAPK signaling pathways mediated by NOD1 and NOD2, RIP2 plays important roles in the host innate immune responses. In the present study, the RIP2 ortholog termed Lc-RIP2 was identified and characterized in large yellow croaker (Larimichthys crocea). It was revealed that Lc-RIP2 is consisted of an open reading frame (ORF) of 1695 bp, encoding a protein of 564 aa, with an N-terminal kinase domain and a C-terminal caspase activation and recruitment domain (CARD). Subcellular localization assays demonstrated that Lc-RIP2 was a cytosolic protein, which was broadly distributed in the examined tissues/organs, and could be induced in response to poly I:C, LPS, PGN, and Pseudomonas plecoglossicida stimulations in vivo according to qRT-PCR analysis. Notably, Lc-RIP2 overexpression in vitro was sufficient to abolish SVCV proliferation in EPC cells, and could significantly induce the activation of NF-κB, IRF3, IRF7, and IFN1 promoters. In addition, luciferase assays found that Lc-RIP2 could cooperate with Lc-MAVS, Lc-TRAF3, Lc-TRAF6, Lc-IRF3, and Lc-IRF7 in NF-κB activation, associate with Lc-TRIF, Lc-MAVS, Lc-TRAF3, Lc-IRF3, and Lc-IRF7 in IRF3 activation, enhance Lc-TRIF, Lc-MAVS, Lc-TRAF3, and Lc-TRAF6 mediated IRF7 activation, and Lc-IRF3 mediated IFN1 activation, whereas suppress NF-κB activation when co-expressed with Lc-TRIF. Co-immunoprecipitation (Co-IP) assays also demonstrated that Lc-RIP2 interacts separately with Lc-TRIF, Lc-MAVS, Lc-TRAF3, Lc-TRAF6, Lc-IRF3, and Lc-IRF7. It is thus collectively indicated that Lc-RIP2 function dominantly in the regulation of the host innate immune signaling.

Antihypertensive Drugs Affect the Association of Systolic Blood Pressure Variability with Outcomes in Patients with Acute Stroke who had Successful Recanalization after Endovascular Treatment.

AIMS: Blood pressure variability (BPV) was associated with the clinical outcomes in patients with acute ischemic stroke (AIS) due to large-vessel occlusion (LVO) after endovascular treatment (EVT). This study aimed to investigate whether the use of antihypertensive drugs could affect this association in patients with AIS-LVO after EVT. METHODS: We retrospectively screened consecutive patients with AIS-LVO who had successful recanalization after EVT and calculated their systolic BPV (SBPV) during the first 24 h after EVT using eight statistical methodologies based on previously published literature. Poor outcome was defined as a modified Rankin Scale score of 3-6 at 90 days. Logistic regression analysis was performed to assess this association, and different prediction models were constructed to assess the effect of the use of antihypertensive drugs. RESULTS: A total of 214 patients were finally included, including 92 (43.0%) with good outcomes, and 136 (63.6%) who received antihypertensive drugs. SBPV indicators were significantly lower in patients with good outcomes versus those with poor outcomes. The logistic analysis showed that all SBPV indicators were consistently associated with poor outcomes (odds ratio, 1.031-1.282, all P＜0.05) in all populations, which was confirmed in patients not using antihypertensive drugs. However, no SBPV indicator was found to be associated with poor outcomes in patients using antihypertensive drugs. Receiver operating characteristic curves showed that the area under the curve (AUC) was larger in the model adjusting for antihypertensive drugs (AUC 0.774-0.783) compared with the one not adjusted for antihypertensive drugs (AUC 0.739-0.754). CONCLUSION: In the anterior circulation of patients with AIS-LVO who had successful recanalization after EVT, the utilization of antihypertensive drugs may have some impact on the relationship between SBPV and clinical outcomes.