bluuebunny/crossref_metadata_2025 huggingface dataset:
The microbiota-gut-brain axis in stress and depression
Authors: Tan Hwei-Ee
Published: April 2023

Humans and animals are evolved to have instinctive physiological responses to threats. The perception of threat by the brain triggers a multitude of changes across the brain and body. A large body of research have demonstrated that our hardwired survival instinct, the stress response, can become maladaptive and promote major depressive disorders and other neuropsychiatric impairments. However, gaps in our understanding of how chronic stress contributes to depression and mental disorders suggest that we also need to consider factors beyond the biology of the host. The unravelling of the structure and function of microorganisms that humans and animals are host to have driven a paradigm shift in understanding the individual as a collective network composed of the host plus microbes. Well over 90% of bacteria in the body reside in the large intestines, and these microbes in the lower gut function almost like an organ in the body in the way it interacts with the host. Importantly, bidirectional interactions between the gut microbiota and the brain (i.e., the two-way microbiota-gut-brain axis) have been implicated in the pathophysiology of mental disorders including depression. Here, in summarizing the emerging literature, we envisage that further research particularly on the efferent brain-gut-microbiota axis will uncover transformative links in the biology of stress and depression.
Energy minimization segmentation model based on MRI images
Authors: Wang Xiuxin , Yang Yuling , Wu Ting , Zhu Hao , Yu Jisheng , Tian Jian , Li Hongzhong
Published: April 2023

Introduction

Medical image segmentation is an important tool for doctors to accurately analyze the volume of brain tissue and lesions, which is important for the correct diagnosis of brain diseases. However, manual image segmentation methods are time-consuming, subjective and lack of repeatability, it needs to develop automatic and reliable methods for image segmentation.

Methods

Magnetic Resonance Imaging (MRI), a non-invasive imaging technique, is commonly used to detect, characterize and quantify tissues and lesions in the brain. Partial volume effect, gray scale in homogeneity, and lesions presents a great challenge for automatic medical image segmentation methods. So, the paper is dedicated to address the impact of partial volume effect and multiple sclerosis lesions on the segmentation accuracy in MRI. The objective function of the improved model and the post-processing method of lesion filling are researched based on the fuzzy clustering space and energy model.

Results

In particular, an energy-minimized segmentation algorithm is proposed. Through experimental verification, the AR-FCM algorithm can better overcome the problem of low segmentation accuracy of the RFCM algorithm for tissue boundary voxels and improve the segmentation accuracy of this algorithm. Meanwhile, a multi-channel input energy-minimization segmentation method with lesion filling and anatomical mapping is further proposed.

Discussion

The feasibility of the lesion filling strategy using post-processing can be confirmed and the segmentation accuracy is increased by comparison experiments.
Candidate Chinese Herbal Medicine Alleviates Methamphetamine Addiction via Regulating Dopaminergic and Serotonergic Pathways
Authors: Ru Qin , Xiong Qi , Tian Xiang , Xu Congyue , Li Can , Chen Lin , Wu Yuxiang
Published: April 2023

Graphical Abstract

Conditioned place preference (CPP) test was used to assess the potential therapeutic effects of CCHM on METH addiction. The active components and hub targets, which were screened by the network pharmacology analysis, were verified by further experiments.
The mTOR inhibitor rapamycin suppresses trigeminal neuropathic pain and p-MKK4/p-p38 mitogen-activated protein kinase-mediated microglial activation in the trigeminal nucleus caudalis of mice with infraorbital nerve injury
Authors: Yeo Ji-Hee , Roh Dae-Hyun
Published: April 2023

Neuropathic pain caused by trigeminal nerve injury is a typical refractory orofacial chronic pain accompanied by the development of hyperalgesia and allodynia. We previously demonstrated that the mammalian target of rapamycin (mTOR) inhibitor rapamycin suppressed orofacial formalin injection-induced nociception; however, the underlying mechanism is unclear, and it is unknown whether it can reduce trigeminal neuropathic pain. In mice, left infraorbital nerve and partial nerve ligation (ION-pNL) was performed using a silk suture (8–0). Fourteen days after surgery, neuropathic pain behavior was examined on a whisker pad and rapamycin (0.1, 0.3, and 1.0 mg/kg) was administered intraperitoneally. Mechanical and cold sensitivities in the orofacial region were quantified using von Frey filaments and acetone solution, respectively. Changes in mTOR and related proteins, such as p-MKK3/6, p-MKK4, p-JNK, p-ERK, p-p38 MAPK, GFAP, and Iba-1, in the trigeminal nucleus caudalis (TNC) or the trigeminal ganglia (TG) tissues were examined via western blot analysis or immunohistochemistry. Mice demonstrated significant mechanical and cold allodynia 2 weeks following ION-pNL injury, both of which were significantly reduced 1 h after the administration of high-dose rapamycin (1.0 mg/kg). In the TG tissue, ION-pNL surgery or rapamycin treatment did not change p-mTOR and p-4EBP1, but rapamycin reduced the increase of p-S6 and S6 induced by ION-pNL. In the TNC tissue, neither ION-pNL surgery nor rapamycin treatment altered p-mTOR, p-S6, and p-4EBP1 expressions, whereas rapamycin significantly decreased the ION-pNL-induced increase in Iba-1 expression. In addition, rapamycin suppressed the increase in p-p38 MAPK and p-MKK4 expressions but not p-MKK3/6 expression. Moreover, p-p38 MAPK-positive cells were colocalized with increased Iba-1 in the TNC. Our findings indicate that rapamycin treatment reduces both mechanical and cold orofacial allodynia in mice with trigeminal neuropathic pain, which is closely associated with the modulation of p-MKK4/p-p38 MAPK-mediated microglial activation in the TNC.
Single and combined associations of blood lead and essential metals with serum lipid profiles in community-dwelling adults
Authors: Wan Heng , Wang Dongmei , Liang Yongqian , He Yajun , Ma Qintao , Li Tingting , He Yingbo , Guo Hanquan , Wang Jiachen , Li Zhao , Lin Xu , Liu Lan , Shen Jie
Published: April 2023

Background

Although several studies have examined the relationships between lead (Pb) exposure and serum lipid profiles, the associations of the metal mixture, including lead (Pb) and essential metals with lipid profiles, remain unclear.

Objective

To investigate the associations of the metal mixture including Pb and essential metals [magnesium (Mg), manganese (Mn), copper (Cu), iron (Fe), zinc (Zn), and calcium (Ca)] with serum lipid profiles [total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C)], as well as the potential interactions among the metals.

Methods

Nine hundred and ninety-eight Chinese community-dwelling adults completed a questionnaire and underwent checkups of anthropometric parameters, serum lipid profile levels (TC, TG, LDL-C, and HDL-C), and blood metal concentrations (Pb, Mg, Mn, Cu, Fe, Zn, and Ca). The multivariable linear regression, weighted quantile sum (WQS) regression, and Bayesian kernel machine regression (BKMR) were applied to evaluate the single and combined associations of blood Pb and essential metals with serum lipid profiles.

Results

In the multivariable linear regression model, the blood Pb was positively associated with TC, LDL-C, and HDL-C (p < 0.05, all), and the blood Mg were positively associated with serum TC, LDL-C, and Ln TG (p < 0.05, all). In the WQS regression and BKMR models, the metal mixture of blood Pb and the essential metals was positively associated with all of the serum lipid profiles. In addition, an inverse U-shaped association of Pb with Ln TG and the positive interactive effect between blood Pb and Mg levels on TC and LDL-C were found.

Conclusion

The levels of blood Pb, together with the essential metals, especially Mg levels, are suggested to be considered when assessing dyslipidemia risk. However, more evidence is still needed to validate the conclusions.
Chronic circadian desynchronization of feeding-fasting rhythm generates alterations in daily glycemia, LDL cholesterolemia and microbiota composition in mice
Authors: Trebucq Laura Lucía , Lamberti Melisa Luciana , Rota Rosana , Aiello Ignacio , Borio Cristina , Bilen Marcos , Golombek Diego Andrés , Plano Santiago Andrés , Chiesa Juan José
Published: April 2023

Introduction

The circadian system synchronizes behavior and physiology to the 24-h light– dark (LD) cycle. Timing of food intake and fasting periods provide strong signals for peripheral circadian clocks regulating nutrient assimilation, glucose, and lipid metabolism. Mice under 12 h light:12 h dark (LD) cycles exhibit behavioral activity and feeding during the dark period, while fasting occurs at rest during light. Disruption of energy metabolism, leading to an increase in body mass, was reported in experimental models of circadian desynchronization. In this work, the effects of chronic advances of the LD cycles (chronic jet-lag protocol, CJL) were studied on the daily homeostasis of energy metabolism and weight gain.

Methods

Male C57 mice were subjected to a CJL or LD schedule, measuring IPGTT, insulinemia, microbiome composition and lipidemia.

Results

Mice under CJL show behavioral desynchronization and feeding activity distributed similarly at the light and dark hours and, although feeding a similar daily amount of food as compared to controls, show an increase in weight gain. In addition, ad libitum glycemia rhythm was abolished in CJL-subjected mice, showing similar blood glucose values at light and dark. CJL also generated glucose intolerance at dark in an intraperitoneal glucose tolerance test (IPGTT), with increased insulin release at both light and dark periods. Low-density lipoprotein (LDL) cholesterolemia was increased under this condition, but no changes in HDL cholesterolemia were observed. Firmicutes/Bacteroidetes ratio was analyzed as a marker of circadian disruption of microbiota composition, showing opposite phases at the light and dark when comparing LD vs. CJL.

Discussion

Chronic misalignment of feeding/fasting rhythm leads to metabolic disturbances generating nocturnal hyperglycemia, glucose intolerance and hyperinsulinemia in a IPGTT, increased LDL cholesterolemia, and increased weight gain, underscoring the importance of the timing of food consumption with respect to the circadian system for metabolic health.
Acute inflammatory reaction during anti-angiogenesis therapy combined with immunotherapy as a possible indicator of the therapeutic effect: Three case reports and literature review
Authors: Lei Yihui , Lin Li , Cheng Shuyu , Shao Qiming , Ding Chenchun , Zuo Renjie , Chen Weiping , Liao Quan , Liu Guoyan
Published: April 2023

The posterior line treatment of unresectable advanced or metastatic gastrointestinal (GI) tumors has always been a challenging point. In particular, for patients with microsatellite stable (MSS)/mismatch repair proficient (pMMR) 0GI tumors, the difficulty of treatment is exacerbated due to their insensitivity to immune drugs. Accordingly, finding a new comprehensive therapy to improve the treatment effect is urgent. In this study, we report the treatment histories of three patients with MSS/pMMR GI tumors who achieved satisfactory effects by using a comprehensive treatment regimen of apatinib combined with camrelizumab and TAS-102 after the failure of first- or second-line regimens. The specific contents of the treatment plan were as follows: apatinib (500 mg/d) was administered orally for 10 days, followed by camrelizumab (200 mg, ivgtt, day 1, 14 days/cycle) and TAS-102 (20 mg, oral, days 1–21, 28 days/cycle). Apatinib (500 mg/d) was maintained during treatment. Subsequently, we discuss the possible mechanism of this combination and review the relevant literature, and introduce clinical trials on anti-angiogenesis therapy combined with immunotherapy.
Diagnostic value of the apparent diffusion coefficient in differentiating malignant from benign endometrial lesions
Authors: Scepanovic Bojana , Andjelic Nikola , Mladenovic-Segedi Ljiljana , Kozic Dusko , Vuleta Dusan , Molnar Una , Nikolic Olivera
Published: April 2023

Introduction

Magnetic resonance imaging (MRI) with its innovative techniques, such as diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC), increases the diagnostic accuracy in distinguishing between malignant and benign lesions of the endometrium. The aim of the study was MRI differentiation between malignant and benign endometrial lesions and correlation with histopathological findings with a special emphasis on quantitative analysis. An additional aim was to correlate the ADC values and histological tumor grades.

Methods

The prospective study included 119 female patients with or without vaginal bleeding and pathological values of endometrial thickness, who underwent MRI examinations. According to MRI reports the patients were divided into 45 suspicious malignant and 74 suspicious benign endometrial lesions. The radiological diagnosis was compared to the histopathological evaluation, which confirmed 37 malignant lesions while the rest were benign.

Results

The mean ADC value for malignant lesions was 0.761 ± 0.13×10−3 mm2/s and for benign lesions was 1.318 ± 0.20×10−3 mm2/s. The ADC values for malignant lesions were expectedly lower than those of benign lesions (p<0.001). The ADC cut-off value was 1.007×10−3 mm2/s with a sensitivity of 100%, specificity of 92.7%, a positive predictive value of 60.3%, and a negative predictive value of 100%. In comparison with the histopathological findings, the sensitivity of MRI was 100%, specificity 90.2%, positive predictive value was 82.2%, and negative predictive value was 100%. Observing the histological grades 1, 2, and 3 of endometrial carcinoma, no statistically significant differences of mean ADC values were found. The mean ADC values for histological tumor grades 1,2 and 3 were 0.803 ± 0.13×10−3 mm2/s, 0.754 ± 0.12×10−3 mm2/s and 0.728 ± 0.13×10−3 mm2/s, respectively.

Conclusion

DWI and ADC values represent clinically useful tools for the differentiation between malignant and benign endometrial lesions with high sensitivity and good specificity, but the results failed to demonstrate their usefulness in differentiating histological grades of endometrial cancer.
Mycosis fungoides and Sézary syndrome: clinical presentation, diagnosis, staging, and therapeutic management
Authors: Miyashiro Denis , Sanches José Antonio
Published: April 2023

Mycosis fungoides (MF) and Sézary syndrome (SS) are cutaneous T-cell lymphomas. MF is the most common cutaneous lymphoma, and it is classified into classic Alibert-Bazin MF, folliculotropic MF, pagetoid reticulosis, and granulomatous slack skin, each with characteristic clinical presentation, histopathological findings, and distinct clinical behaviors. SS is an aggressive leukemic variant of cutaneous lymphoma, and it is characterized by erythroderma, lymphadenopathy, and peripheral blood involvement by malignant cells. There is a wide range of dermatological manifestations of MF/SS, and prompt recognition is essential for early diagnosis. Skin biopsy for histopathology and immunohistochemical analysis is imperative to confirm the diagnosis of MF/SS. Histopathology may also provide information that may influence prognosis and treatment. Staging follows the TNMB system. Besides advanced stage, other factors associated with poorer prognosis are advanced age, male gender, folliculotropism in histopathology of patients with infiltrated plaques and tumors in the head and neck region, large cell transformation, and elevated lactate dehydrogenase. Treatment is divided into skin-directed therapies (topical treatments, phototherapy, radiotherapy), and systemic therapies (biological response modifiers, targeted therapies, chemotherapy). Allogeneic bone marrow transplantation and extracorporeal photopheresis are other treatment modalities used in selected cases. This review discusses the main clinical characteristics, the histopathological/immunohistochemical findings, the staging system, and the therapeutic management of MF/SS.
Circular RNAs: pivotal role in the leukemogenesis and novel indicators for the diagnosis and prognosis of acute myeloid leukemia
Authors: Rahmati Atefe , Mafi Alireza , Soleymani Firooze , Babaei Aghdam Zahra , Masihipour Niloufar , Ghezelbash Behrooz , Asemi Reza , Aschner Michael , Vakili Omid , Homayoonfal Mina , Asemi Zatollah , Sharifi Mehran , Azadi Abbas , Mirzaei Hamed , Aghadavod Esmat
Published: April 2023

Acute myeloid leukemia (AML) is an aggressive hematological malignancy and affected patients have poor overall survival (OS) rates. Circular RNAs (circRNAs) are a novel class of non-coding RNAs (ncRNAs) with a unique loop structure. In recent years, with the development of high-throughput RNA sequencing, many circRNAs have been identified exhibiting either up-regulation or down-regulation in AML patients compared with healthy controls. Recent studies have reported that circRNAs regulate leukemia cell proliferation, stemness, and apoptosis, both positively and negatively. Additionally, circRNAs could be promising biomarkers and therapeutic targets in AML. In this study, we present a comprehensive review of the regulatory roles and potentials of a number of dysregulated circRNAs in AML.
Construction of cancer- associated fibroblasts related risk signature based on single-cell RNA-seq and bulk RNA-seq data in bladder urothelial carcinoma
Authors: Liu Yunxun , Jian Jun , Zhang Ye , Wang Lei , Liu Xiuheng , Chen Zhiyuan
Published: April 2023

Background

The ability of cancer-associated fibroblasts (CAFs) to encourage angiogenesis, tumor cell spread, and increase treatment resistance makes them pro-tumorigenic. We aimed to investigate the CAF signature in Bladder urothelial carcinoma (BLCA) and, for clinical application, to build a CAF-based risk signature to decipher the immune landscape and screen for suitable treatment BLCA samples.

Methods

CAF-related genes were discovered by superimposing CAF marker genes discovered from single-cell RNA-seq (scRNA-seq) data taken from the GEO database with CAF module genes discovered by weighted gene co-expression network analysis (WGCNA) using bulk RNA-seq data from TCGA. After identifying prognostic genes related with CAF using univariate Cox regression, Lasso regression was used to build a risk signature. With microarray data from the GEO database, prognostic characteristics were externally verified. For high and low CAF-risk categories, immune cells and immunotherapy responses were analyzed. Finally, a nomogram model based on the risk signature and prospective chemotherapeutic drugs were examined.

Results

Combining scRNA-seq and bulk-seq data analysis yielded a total of 124 CAF-related genes. LRP1, ANXA5, SERPINE2, ECM1, RBP1, GJA1, and FKBP10 were the seven BLCA prognostic genes that remained after univariate Cox regression and LASSO regression analyses. Then, based on these genes, prognostic characteristics were created and validated to predict survival in BLCA patients. Additionally, risk signature had a strong correlation with known CAF scores, stromal scores, and certain immune cells. The CAF-risk signature was identified as an independent prognostic factor for BLCA using multifactorial analysis, and its usefulness in predicting immunotherapy response was confirmed. Based on risk classification, we projected six highly sensitive anticancer medicines for the high-risk group.

Conclusion

The prognosis of BLCA may be accurately predicted using CAF-based risk signature. With a thorough understanding of the BLCA CAF-signature, it might be able to explain the BLCA patients’ response to immunotherapy and identify a potential target for BLCA treatment.
The diagnostic accuracy of diabetes retinopathy screening by ophthalmic clinical officers, ophthalmic nurses and county ophthalmologists against a retina specialist in 2 selected county referral hospitals, Kenya
Authors: Ong’ang’o Jane Rahedi , Mashedi Olga , Gichangi Micheal , Kiplimo Richard , Nyamori Joseph , Alwenya Kennedy
Published: April 2023

Background

Diabetes is rapidly becoming a major cause of blindness among Kenyans, with the prevalence of any form of diabetes retinopathy (DR) ranging from 36% to 41%. Globally DR leads as a cause of vision loss in working age adults. In Kenya, specialized examinations are only available at national and some county referral hospitals through retina specialists, ophthalmologists or trained technicians. Thus, low coverage of retinal assessment and inadequate access to this service. An innovative DR fundus camera screening service run by ophthalmic nurses (ONs), ophthalmic clinical officers (OCOs) and county ophthalmologists was established since 2018.

Objectives

The purpose of this study was to investigate the diagnostic accuracy of DR digital retinal camera screening by ONs, OCOs and county ophthalmologist against that of a retina specialist measured by sensitivity and specificity as the primary outcomes.

Methods

Cross sectional study conducted at 2 referral hospitals in Kenya. Using a Canon CR-2AF digital retinal camera patients with diabetes had a standard single shot of 45 degree view of the retina captured as image in each eye. This was graded for DR using the International Clinical Diabetic Retinopathy (ICDR) severity scale. All photos taken by the first graders (ON/OCO) were later assessed by the county hospital ophthalmologist who was blinded to their readings. The third grader (retina specialist) similarly was blinded to the readings of the first and second graders and assessed all the images from the 2 hospitals also using ICDR.

Results

A total of 308 patients with diabetes (median age 58 IQR 56-60, 53% female) were enrolled in the study. Sensitivity to identify any DR was (81.3%, 80.6%, and 81.54% for the OCO, ON and county ophthalmologist respectively). The corresponding specificities were 92.7%, 92.8% and 92.59%. Analysis of diagnostic accuracy of non-sight threatening DR against sight threatening DR revealed lower sensitivity for the three cadre groups although specificity remained high.

Conclusions

In this study, ON and OCO with basic training in DR screening and photo grading performed screening of DR with high specificity. However, the sensitivity to detect sight threatening DR was generally low by all the cadres which may leave severe forms of DR undetected.
Mesenchymal stem cells therapy for acute kidney injury: A systematic review with meta-analysis based on rat model
Authors: Wanyan Pingping , Wang Xin , Li Nenglian , Huang Yong , She Yali , Zhang Li
Published: April 2023

Objective: To systematically evaluate the efficacy of mesenchymal stem cells (MSCs) for acute kidney injury (AKI) in preclinical studies and to explore the optimal transplantation strategy of MSCs by network meta-analysis with the aim of improving the efficacy of stem cell therapy.

Methods: Computer searches of PubMed, Web of Science, Cochrane, Embase, CNKI, Wanfang, VIP, and CBM databases were conducted until 17 August 2022. Literature screening, data extraction and quality evaluation were performed independently by two researchers.

Results and Discussion: A total of 50 randomized controlled animal studies were included. The results of traditional meta-analysis showed that MSCs could significantly improve the renal function and injured renal tissue of AKI rats in different subgroups. The results of network meta-analysis showed that although there was no significant difference in the therapeutic effect between different transplant routes and doses of MSCs, the results of surface under the cumulative ranking probability curve (SUCRA) showed that the therapeutic effect of intravenous transplantation of MSCs was better than that of arterial and intrarenal transplantation, and the therapeutic effect of high dose (>1×106) was better than that of low dose (≤1×106). However, the current preclinical studies have limitations in experimental design, measurement and reporting of results, and more high-quality studies, especially direct comparative evidence, are needed in the future to further confirm the best transplantation strategy of MSCs in AKI.

Systematic Review Registration: identifier https://CRD42022361199, https://www.crd.york.ac.uk/prospero.
Development and validation of a machine learning-based detection system to improve precision screening for medication errors in the neonatal intensive care unit
Authors: Yalçın Nadir , Kaşıkcı Merve , Çelik Hasan Tolga , Allegaert Karel , Demirkan Kutay , Yiğit Şule , Yurdakök Murat
Published: April 2023

Aim: To develop models that predict the presence of medication errors (MEs) (prescription, preparation, administration, and monitoring) using machine learning in NICU patients.

Design: Prospective, observational cohort study randomized with machine learning (ML) algorithms.

Setting: A 22-bed capacity NICU in Ankara, Turkey, between February 2020 and July 2021.

Results: A total of 11,908 medication orders (28.9 orders/patient) for 412 NICU patients (5.53 drugs/patient/day) who received 2,280 prescriptions over 32,925 patient days were analyzed. At least one physician-related ME and nurse-related ME were found in 174 (42.2%) and 235 (57.0%) of the patients, respectively. The parameters that had the highest correlation with ME occurrence and subsequently included in the model were: total number of drugs, anti-infective drugs, nervous system drugs, 5-min APGAR score, postnatal age, alimentary tract and metabolism drugs, and respiratory system drugs as patient-related parameters, and weekly working hours of nurses, weekly working hours of physicians, and number of nurses’ monthly shifts as care provider-related parameters. The obtained model showed high performance to predict ME (AUC: 0.920; 95% CI: 0.876–0.970) presence and is accessible online (http://softmed.hacettepe.edu.tr/NEO-DEER_Medication_Error/).

Conclusion: This is the first developed and validated model to predict the presence of ME using work environment and pharmacotherapy parameters with high-performance ML algorithms in NICU patients. This approach and the current model hold the promise of implementation of targeted/precision screening to prevent MEs in neonates.

Clinical Trial Registration:ClinicalTrials.gov, identifier NCT04899960.
Study on the liver Drug’s dominant metabolic enzymes for six effective components of the Huang qi Liuyi decoction
Authors: Wang Qun , Tang Tiantian , Wu Zengguang , Yang Hong , Gao Yuan , Zhang Shiyu , Song Xinli , Chen Xiaolan
Published: April 2023

Objective: To investigate the dominant metabolic enzymes of six effective components (astragaloside IV, glycyrrhizic acid, calycosin-glucuronide, formononetin, ononin, calycosin-7-O-β-D- glucoside) of Huangqi Liuyi decoction extract (HQD).

Methods: Mouse liver microsomes were prepared. The effects of specific inhibitors of CYP450 enzymes on the metabolism of six effective components of HQD were studied using liver microsomal incubation in vitro.

Results: The chemical inhibitors of CYP2C37 inhibit the metabolism of glycyrrhizic acid and astragaloside IV. Formononetin and astragaloside IV metabolism is inhibited by the chemical inhibitors of CYP2C11. The chemical inhibitors of CYP2E1 and CYP1A2 inhibit the metabolism of calycosin-glucuronide. Chemical CYP3A11 inhibitors prevent formononetin and glycyrrhizic acid from being metabolized. However, no inhibitor significantly affected the metabolism of ononin and calycosin-7-O-β-D-glucoside.

Conclusion: CYP2C37 may be involved in the metabolism of astragaloside IV and glycyrrhizic acid, the metabolism of astragaloside IV and formononetin may be related to CYP2C11, the metabolism of calycosin-glucuronide may be related to CYP1A2 and CYP2E1, and CYP3A11 may be involved in the metabolism of glycyrrhizic acid and formononetin. This research provides an experimental basis for exploring the pharmacokinetic differences caused by metabolic enzymes.
Introduction of managed entry agreements in Korea: Problem, policy, and politics
Authors: Kim Hyungmin , Godman Brian , Kwon Hye-Young , Hong Song Hee
Published: April 2023

Objectives: This study aimed to understand Managed Entry Agreements (MEAs) in Korea through the framework of three streams of the policy window model and its practical management and impact on pricing and reimbursement scheme.

Methods: An extensive literature review based on Kingdon’s model was conducted. We also performed descriptive analyses of MEA implementation using data on medicines listed in Korea and compared its MEA scheme with four different countries.

Results: As per problem streams, patients with rare disease or cancers have considerable difficulties in affording their medicines and this has challenged the drug benefit system and raised an issue of patient’s access. Policy streams highlighted that MEAs were introduced as a benefit enhancement plan for four major diseases since January 2014. MEAs have also been strengthened as a bypass mechanism to expand the insurance coverage especially for new premium-priced medicines under Moon Care (Listing all non-listed services). In descriptive analysis of MEAs, a total of 48 medicines were contracted as MEAs from January 2014 to December 2020, accounting for 73.4% of listed medicines for cancer or rare diseases and 97.9% of the cases were finance-based contracts. Meanwhile, outcome-based contracts such as CED accounted for only 2.1%. The application of MEAs differs across countries, resulting in a kappa coefficient of 0.00–0.14 (United Kingdom 0.03, Italy 0.00, Australia 0.14), indicating a lack of consistency compared to South Korea.

Conclusion: MEAs, which were introduced as a bypass mechanism, have now superseded the standard process for anticancer agents or orphan drugs. Further studies are needed to evaluate the impact of the confidential agreements and effectiveness of new high-priced medicines with limited clinical data at launch.
Tailed skyrmions—An obscure branch of magnetic solitons
Authors: Kuchkin Vladyslav M. , Kiselev Nikolai S. , Rybakov Filipp N. , Bessarab Pavel F.
Published: April 2023

We report tailed skyrmions—a new class of stable soliton solutions of the 2D chiral magnet model. Tailed skyrmions have elongated shapes and emerge in a narrow range of fields near the transition between the spin spirals and the saturated state. We analyze the stability range of these solutions in terms of external magnetic field and magnetocrystalline anisotropy. We calculate minimum energy paths and homotopies (continuous transitions) between tailed skyrmions of the same topological charge. The discovery of tailed skyrmions extends the diversity of already known solutions. This is illustrated by solitons with complex morphology, such as tailed skyrmion bags with and without chiral kinks.
Heart rate variability in different sleep stages is associated with metabolic function and glycemic control in type 2 diabetes mellitus
Authors: Cheng Wenquan , Chen Hongsen , Tian Leirong , Ma Zhimin , Cui Xingran
Published: April 2023

Introduction: Autonomic nervous system (ANS) plays an important role in the exchange of metabolic information between organs and regulation on peripheral metabolism with obvious circadian rhythm in a healthy state. Sleep, a vital brain phenomenon, significantly affects both ANS and metabolic function.

Objectives: This study investigated the relationships among sleep, ANS and metabolic function in type 2 diabetes mellitus (T2DM), to support the evaluation of ANS function through heart rate variability (HRV) metrics, and the determination of the correlated underlying autonomic pathways, and help optimize the early prevention, post-diagnosis and management of T2DM and its complications.

Materials and methods: A total of 64 volunteered inpatients with T2DM took part in this study. 24-h electrocardiogram (ECG), clinical indicators of metabolic function, sleep quality and sleep staging results of T2DM patients were monitored.

Results: The associations between sleep quality, 24-h/awake/sleep/sleep staging HRV and clinical indicators of metabolic function were analyzed. Significant correlations were found between sleep quality and metabolic function (|r| = 0.386 ± 0.062, p < 0.05); HRV derived ANS function showed strengthened correlations with metabolic function during sleep period (|r| = 0.474 ± 0.100, p < 0.05); HRV metrics during sleep stages coupled more tightly with clinical indicators of metabolic function [in unstable sleep: |r| = 0.453 ± 0.095, p < 0.05; in stable sleep: |r| = 0.463 ± 0.100, p < 0.05; in rapid eye movement (REM) sleep: |r| = 0.453 ± 0.082, p < 0.05], and showed significant associations with glycemic control in non-linear analysis [fasting blood glucose within 24 h of admission (admission FBG), |r| = 0.420 ± 0.064, p < 0.05; glycated hemoglobin (HbA1c), |r| = 0.417 ± 0.016, p < 0.05].

Conclusions: HRV metrics during sleep period play more distinct role than during awake period in investigating ANS dysfunction and metabolism in T2DM patients, and sleep rhythm based HRV analysis should perform better in ANS and metabolic function assessment, especially for glycemic control in non-linear analysis among T2DM patients.
Divergence of functions and expression patterns of soybean bZIP transcription factors
Authors: Yue Lin , Pei Xinxin , Kong Fanjiang , Zhao Lin , Lin Xiaoya
Published: April 2023

Soybean (Glycine max) is a major protein and oil crop. Soybean basic region/leucine zipper (bZIP) transcription factors are involved in many regulatory pathways, including yield, stress responses, environmental signaling, and carbon-nitrogen balance. Here, we discuss the members of the soybean bZIP family and their classification: 161 members have been identified and clustered into 13 groups. Our review of the transcriptional regulation and functions of soybean bZIP members provides important information for future study of bZIP transcription factors and genetic resources for soybean breeding.
Rice pest identification based on multi-scale double-branch GAN-ResNet
Authors: Hu Kui , Liu YongMin , Nie Jiawei , Zheng Xinying , Zhang Wei , Liu Yuan , Xie TianQiang
Published: April 2023

Rice production is crucial to the food security of all human beings, and how rice pests and diseases can be effectively prevented in and timely detected is a hotspot issue in the field of smart agriculture. Deep learning has become the preferred method for rice pest identification due to its excellent performance, especially in the aspect of autonomous learning of image features. However, in the natural environment, the dataset is too small and vulnerable to the complex background, which easily leads to problems such as overfitting, and too difficult to extract the fine features during the process of training. To solve the above problems, a Multi-Scale Dual-branch structural rice pest identification model based on a generative adversarial network and improved ResNet was proposed. Based on the ResNet model, the ConvNeXt residual block was introduced to optimize the calculation ratio of the residual blocks, and the double-branch structure was constructed to extract disease features of different sizes in the input disease images, which it adjusts the size of the convolution kernel of each branch. In the complex natural environment, data pre-processing methods such as random brightness and motion blur, and data enhancement methods such as mirroring, cropping, and scaling were used to allow the dataset of 5,932 rice disease images captured from the natural environment to be expanded to 20,000 by the dataset in this paper. The new model was trained on the new dataset to identify four common rice diseases. The experimental results showed that the recognition accuracy of the new rice pest recognition model, which was proposed for the first time, improved by 2.66% compared with the original ResNet model. Under the same experimental conditions, the new model had the best performance when compared with classical networks such as AlexNet, VGG, DenseNet, ResNet, and Transformer, and its recognition accuracy could be as high as 99.34%. The model has good generalization ability and excellent robustness, which solves the current problems in rice pest identification, such as the data set is too small and easy to lead to overfitting, and the picture background is difficult to extract disease features, and greatly improves the recognition accuracy of the model by using a multi-scale double branch structure. It provides a superior solution for crop pest and disease identification.
Grapevine double cropping: a magic technology
Authors: Lu Guilong , Zhang Kai , Que Youxiong , Li Yanfeng
Published: April 2023

Grapevine is one of the most important fruit trees in the world, but it is often threatened by various biotic and abiotic stresses in production, resulting in decreased yield and quality. Grapevine double cropping in one year is a kind of preparatory and artificial control technology, which can not only save the loss of natural disasters, but also plays an important role in staggering the peak to market, thus increasing yield and improving the quality of grape fruit. This perspective provides a concise discussion of the physiological basis, the main determinants, and their impacts on yield and fruit quality of grapevine double cropping. We also highlight the current challenges around this theme and prospect its application in the future.
The effect of productive vocabulary knowledge on second language comprehension
Authors: Allal-Sumoto Takara Kenza , Miyoshi Kiyofumi , Mizuhara Hiroaki
Published: April 2023

Second language learners tend to focus more on learning the meaning of vocabulary than on how to use it in their speech and writing. Although comprehensive vocabulary knowledge is necessary for understanding sentences, productive vocabulary knowledge may also have a positive impact on sentence comprehension. Most studies examining the relationship between production and comprehension have compared these abilities between participants or evaluated unrelated criteria between tasks, which may be insufficient for examining the direct effects of productive knowledge on sentence comprehension. Our study investigates changes in sentence comprehension speed during listening, and we used a within-subjects comparison to examine the effect of productive vocabulary knowledge or the lack thereof. We applied generalized linear mixed models to investigate productive vocabulary knowledge effects by partialing out other influential factors, such as confidence, frequency of target words, stimulus duration, and individual differences. The results showed that the sentences with a producible phrase were processed faster than the sentences that included phrases with only comprehensive knowledge or no comprehension. The effect of productive vocabulary knowledge on the speed of sentence comprehension was directly examined with a within-subject comparison, and its contribution was clearly found. This study emphasizes the value of productive vocabulary knowledge acquisition in enhancing the speed of sentence comprehension.
More than words: Speech production in first-episode psychosis predicts later social and vocational functioning
Authors: Mackinley Michael , Limongi Roberto , Silva Angélica María , Richard Julie , Subramanian Priya , Ganjavi Hooman , Palaniyappan Lena
Published: April 2023

Background

Several disturbances in speech are present in psychosis; however, the relationship between these disturbances during the first-episode of psychosis (FEP) and later vocational functioning is unclear. Demonstrating this relationship is critical if we expect speech and communication deficits to emerge as targets for early intervention.

Method

We analyzed three 1-min speech samples using automated speech analysis and Bayes networks in an antipsychotic-naive sample of 39 FEP patients and followed them longitudinally to determine their vocational status (engaged or not engaged in employment education or training—EET vs. NEET) after 6–12 months of treatment. Five baseline linguistic variables with prior evidence of clinical relevance (total and acausal connectives use, pronoun use, analytic thinking, and total words uttered in a limited period) were included in a Bayes network along with follow-up NEET status and Social and Occupational Functioning Assessment Scale (SOFAS) scores to determine dependencies among these variables. We also included clinical (Positive and Negative Syndrome Scale 8-item version (PANSS-8)), social (parental socioeconomic status), and cognitive features (processing speed) at the time of presentation as covariates.

Results

The Bayes network revealed that only total words spoken at the baseline assessment were directly associated with later NEET status and had an indirect association with SOFAS, with a second set of dependencies emerging among the remaining linguistic variables. The primary (speech-only) model outperformed models including parental socioeconomic status, processing speed or both as latent variables.

Conclusion

Impoverished speech, even at subclinical levels, may hold prognostic value for functional outcomes and warrant consideration when providing measurement based care for first-episode psychosis.
Case series: Cariprazine in early-onset schizophrenia
Authors: Ivanova Elena , Maslinkova Desislava , Polnareva Nadia , Milanova Vihra
Published: April 2023

Introduction

Negative symptoms are part of the clinical manifestations of schizophrenia and their presence is associated with a poorer prognosis, significantly limited vocational opportunities, impaired quality of life and social functioning. In the clinical practice, treatment of negative symptoms in patients with schizophrenia, is a challenge. Cariprazine is a novel partial agonist of D3 and D2 receptors, and shows a high affinity for D3, with good tolerability, good response to schizophrenic symptoms and limited side effects. We present two cases of young patients with predominantly negative symptoms during treatment with an atypical antipsychotic, administered in a stable dose and therapeutic range, and for at least 4 weeks prior to the Cariprazine switch.

Methods

Two patients (men aged 21 and 22) with schizophrenia, exhibiting predominantly negative symptoms, are presented. Their diagnosis was based on, DSM-5 criteria (295.10).

Patients were treated with Cariprazine at a daily dose of 4.5 mg. They were followed for a period of 18 months and assessed with Positive and Negative Syndrome Scale (PANSS), Global Assessment of Functioning (GAF) and Clinical Global Impression-Severity (CGI-S), at the fourth week of initiation of treatment with Cariprazine, at 6 months, at 12 months and at 18 months. Their mean initial value was 75.5 on PANSS, 4.0 on CGI-S, and 52.5 on GAF. Both patients were treated with stable doses of atypical antipsychotic–Risperidone at a daily dose of 4,5 mg. Cross-titration to Cariprazine was initiated, from 1.5 mg daily dose up to 4,5 mg daily dose, during a period of 2 weeks.

Results

After 18 months of treatment with Cariprazine at a daily dose of 4.5 mg, the following results were reported: mean value was 57.5 on PANSS, 3.0 on CGI-S, and 74.5 on GAF. The overall PANSS mean score decreased by 23.8%, the CGI-S mean score improved by 25% and the mean GAF score increased by 29.5%. The positive PANSS subscale score decreased minimally, from 20 to 16, while for the negative subscale the improvement was 29.8%.

Cariprazine was well tolerated by patients and no side effects were observed from it during therapy.

Discussion

After 18 months Cariprazine succeeded in improving negative symptoms, global functioning, and global clinical impression. In young schizophrenic patients with a predominance of negative symptoms, the cariprazine may be a successful alternative.
Health service behaviors of migrants: A conceptual framework
Authors: Peng Boli , Ling Li
Published: April 2023

Universal health coverage is vital to the World Health Organization’s (WHO’s) efforts to ensure access to health as a human right. However, it has been reported that migrants, including both international immigrants and internal migrants, underuse health services. Establishing a conceptual framework to facilitate research on the health service behaviors (HSB) of migrants is particularly important. Many theoretical frameworks explaining the general population’s HSB have been published; however, most theoretical frameworks on migrants’ HSB only focus on international immigrants without the inclusion of internal migrants. Of note, internal migrants are much more abundant than immigrants, and this group faces similar barriers to HSB as immigrants do. Based on theoretical frameworks of immigrants’ HSB and Anderson’s behavior model, the author proposes a new conceptual framework of migrants’ HSB that includes both immigrants and internal migrants. The new conceptual framework divides the determinants into macro-structural or contextual factors, health delivery system characteristics, and characteristics of the population at risk and describes subgroup-specific factors. The author added some variables and reclassified variables in some dimensions, including characteristics of health delivery systems and access to healthcare. The characteristics of health delivery systems comprise the volume, organization, quality, and cost of the health delivery system, while the characteristics of access to healthcare include time accessibility, geographic accessibility, and information accessibility. The outcomes of HSB have been expanded, and relationships between them have been reported. The mediating effects of some variables have also been described. This conceptual framework can facilitate a deep and comprehensive understanding of the HSB determination process for migrants, including internal migrants.