Influence of slow and rapid weight loss periods on physiological performance, mood state and sleep quality in male freestyle wrestlers: a study from Sichuan Province, China.

Objective: This study aims to investigate the changes in physiological performance, mental state and sleep quality during the weight reduction phase prior to competition in male freestyle wrestlers. Methods: This study included 16 male freestyle wrestlers from Sichuan Province, China. Participants were evaluated at three time points: the first day of slow weight reduction (T1, March 26), the first day of rapid weight reduction (T2, April 26) and the day before the competition (T3, May 3), and measurements were taken for physiological performance, mood state and sleep quality. Results: The most relevant findings indicated the following: Morning heart rate, creatine kinase and fatigue scores increased by 12.6, 64.6, and 19.0%, respectively, from T1 to T2 (p < 0.05), and decreased by 14.1, 36.6, and 16.8%, respectively, from T2 to T3 (p < 0.05). Hemoglobin and testosterone levels decreased by 3.0 and 16.8%, respectively, from T1 to T3 (p < 0.05), and by 2.9 and 18.2%, respectively, from T2 to T3 (p < 0.05); The secondary findings revealed the following: The total mood disturbance scores decreased by 3.8% from T2 to T3 (p = 0.072), positive mood scores decreased by 9.0% from T1 to T2 (p = 0.090), the Pittsburgh Sleep Quality Index total scores increased by 14.4% from T1 to T2 (p = 0.323) and total work output and average power output decreased by 7.3 and 7.8%, respectively, from T1 to T3 (p = 0.067, p = 0.052); Regression analyses predicted negative mood (Y 1 = 62.306-0.018 × maximum power output) and sleep quality (Y 2 = 2.527 + 0.278 × Immunoglobulin G) during the weight reduction period. Conclusion: The combined slow and rapid weight reduction approach effectively minimized body fat in athletes with limited effect on their physiological performance and sleep quality. However, the effects were adverse on certain health variables and anaerobic power in Chinese male freestyle wrestlers. The identified correlations between negative mood and maximum power, and between sleep quality and immunoglobulin G, shed new light on factors influencing athletes' well-being during weight reduction, and underscored the need for careful monitoring of physiological variables in future weight management strategies.

Identification of mitophagy-related genes and analysis of immune infiltration in the astrocytes based on machine learning in the pathogenesis of major depressive disorder.

BACKGROUNDS: Major depressive disorder (MDD) is a pervasive mental and mood disorder with complicated and heterogeneous etiology. Mitophagy, a selective autophagy of cells, specifically eliminates dysfunctional mitochondria. The mitochondria dysfunction in the astrocytes is regarded as a critical pathogenetic mechanism of MDD. However, studies on the mitophagy of astrocytes in MDD are scarce. To explore the impact of mitophagy on the astrocytes, we used bioinformatic methods to analyze the correlation between astrocyte-related genes and mitophagy-related genes in MDD. METHODS: The microarray dataset of MDD was downloaded from the Gene Expression Omnibus database and identified astrocyte- and mitophagy-related differentially expressed genes (AMRDEGs). We used three machine learning algorithms to identify hub AMRDEGs and constructed a diagnostic prediction model. Also, we analyzed transcription factor-gene and gene-microRNA interaction networks, and the immune infiltration in MDD and healthy controls. Besides, we performed consensus clustering analysis, immune infiltration analysis, and gene set variation analysis of MDD samples. RESULTS: The present research identified 3 hub AMRDEGs (GRN, NDUFAF4, and SNCA), and a good diagnostic model with potential clinical applications was constructed and validated. Besides, we identified 6 transcription factors and 14 microRNAs. The immune infiltration analysis showed that MDD was closely related to immune cells. Gene set variant analysis showed that MDD was related to immune and mitochondrial metabolism and inflammatory signaling pathways. CONCLUSIONS: We identified 3 hub AMRDEGs, new biomarkers for treating and diagnosing MDD and associated with immuno-inflammation. Our research provides new insights into the early diagnosis and treatment of MDD.

Novel insight into astrocyte-mediated gliotransmission modulates the synaptic plasticity in major depressive disorder.

Major depressive disorder (MDD) is a form of glial cell-based synaptic dysfunction disease in which glial cells interact closely with neuronal synapses and perform synaptic information processing. Glial cells, particularly astrocytes, are active components of the brain and are responsible for synaptic activity through the release gliotransmitters. A reduced density of astrocytes and astrocyte dysfunction have both been identified the brains of patients with MDD. Furthermore, gliotransmission, i.e., active information transfer mediated by gliotransmitters between astrocytes and neurons, is thought to be involved in the pathogenesis of MDD. However, the mechanism by which astrocyte-mediated gliotransmission contributes to depression remains unknown. This review therefore summarizes the alterations in astrocytes in MDD, including astrocyte marker, connexin 43 (Cx43) expression, Cx43 gap junctions, and Cx43 hemichannels, and describes the regulatory mechanisms of astrocytes involved in synaptic plasticity. Additionally, we investigate the mechanisms acting of the glutamatergic, gamma-aminobutyric acidergic, and purinergic systems that modulate synaptic function and the antidepressant mechanisms of the related receptor antagonists. Further, we summarize the roles of glutamate, gamma-aminobutyric acid, d-serine, and adenosine triphosphate in depression, providing a basis for the identification of diagnostic and therapeutic targets for MDD.

Efficacy of ginsenoside Rg1 on rodent models of depression: A systematic review and meta-analysis.

RATIONALE: Depression is a prevalent psychiatric disease, and ginsenoside Rg1 is a bioactive compound extracted from the root of Panax ginseng C.A.Mey. To systematically investigate the effectiveness of Rg1 in rodent models of depression and provide evidence-based references for treating depression. METHODS: Electronic searches for rodent studies were performed from inception to October 2022, e.g., PUBMED and EMBASE. Data extraction and quality evaluation were performed for the references, and meta-analysis was performed on the selected data using Review Manager 5.3.5. The outcomes were analyzed via a random-effect model and presented as mean difference (MD) with 95% confidence intervals (CIs). RESULTS: A total of 24 studies and 678 animals were included in this meta-analysis. Rg1 remarkably improved depressive-like symptoms of depressed rodents, including the sucrose preference test (25.08, 95% CI: 20.17-30.00, Z = 10.01, P < 0.00001), forced swimming test (MD = -37.69, 95% CI: (-45.18, -30.2); Z = 9.86, P < 0.00001), and the tail suspension test (MD = -22.93, seconds, 95% CI: (-38.49, -7.37); Z = 2.89, P = 0.004). CONCLUSIONS: The main antidepressant mechanism of Rg1 was concluded to be the neurotransmitter system, oxidant stress system, and inflammation. Conclusively, this study indicated the possible protective and therapeutic effects of Rg1 for treating depression via multiple mechanisms.

Water-filtered infrared A radiation hyperthermia combined with immunotherapy for advanced gastrointestinal tumours.

This study pioneered the use of WIRA whole-body infrared hyperthermia combined with ICI therapy to treat GIT and verified the feasibility and safety of HIT. The final results showed a DCR of 55.6%, with a median PFS of 53.5 days, median OS of 134 days, and an irAE incidence of 22.2%. Therefore, we believe that HIT can exert multiple synergistic sensitisation effects, thereby providing clinical benefits to patients with advanced GITs, increasing overall safety, and improving patients' QOL.

INTRODUCTION: This study aimed to validate the effectiveness, safety and feasibility of water­filtered infrared A radiation (WIRA) whole­body hyperthermia combined with immune checkpoint inhibitor (ICI) therapy (HIT) and evaluate the real­world clinical application prospects. METHODS: This open­label single­arm phase 2 clinical trial (NCT06022692) aimed to enrol advanced gastrointestinal tumour (GIT) patients with the MSS/pMMR phenotype. The patients were treated with whole­body hyperthermia on Days 1 and 8 of each HIT cycle along with administration of tislelizumab on Day 2. RESULTS: Between 1 June 2020 and 31 May 2022, 18 patients were enrolled in the study, including those with gastric cancer (n = 6), colon cancer (n = 7), rectal cancer (n = 3) and appendiceal cancer (n = 2). As of 19 May 2023, 17 of the 18 patients had died, including 14 deaths caused by tumour progression and three deaths caused by diseases other than cancer, while one patient was still undergoing follow­up. In terms of efficacy, the median DCR was 55.6%, while the median PFS and OS were 53.5 days and 134 days, respectively. Four patients (22.2%) experienced immune­related adverse events, and none of the patients reported grade 3 or higher irAEs. Hyperthermia was followed by an increase in the number of tumour immune­activated cells. CONCLUSIONS: HIT can provide survival benefits in patients with GITs by activating antitumour immune function and shows good safety and feasibility.

Impacts of microbiota and its metabolites through gut-brain axis on pathophysiology of major depressive disorder.

Major depressive disorder (MDD) is characterized by a high rate of recurrence and disability, which seriously affects the quality of life of patients. That's why a deeper understanding of the mechanisms of MDD pathology is an urgent task, and some studies have found that intestinal symptoms accompany people with MDD. The microbiota-gut-brain axis is the bidirectional communication between the gut microbiota and the central nervous system, which was found to have a strong association with the pathogenesis of MDD. Previous studies have focused more on the communication between the gut and the brain through neuroendocrine, neuroimmune and autonomic pathways, and the role of gut microbes and their metabolites in depression is unclear. Metabolites of intestinal microorganisms (e.g., tryptophan, kynurenic acid, indole, and lipopolysaccharide) can participate in the pathogenesis of MDD through immune and inflammatory pathways or by altering the permeability of the gut and blood-brain barrier. In addition, intestinal microbes can communicate with intestinal neurons and glial cells to affect the integrity and function of intestinal nerves. However, the specific role of gut microbes and their metabolites in the pathogenesis of MDD is not well understood. Hence, the present review summarizes how gut microbes and their metabolites are directly or indirectly involved in the pathogenesis of MDD.

Enhanced photocatalytic U(VI) reduction via double internal electric field in CoWO4/covalent organic frameworks p-n heterojunction.

Photoreduction of highly toxic U(VI) to less toxic U(IV) is crucial for mitigating radioactive contamination. Herein, a CoWO4/TpDD p-n heterojunction is synthesized, with TpDD serving as the n-type semiconductor substrate and CoWO4 as the p-type semiconductor grown in situ on its surface. The Fermi energy difference between TpDD and CoWO4 provides the electrochemical potential for charge-hole separation. Moreover, the Coulombic forces from the distinct carrier types between the two materials synergistically facilitate the transfer of electrons and holes. Hence, an internal electric field directed from TpDD to CoWO4 is established. Under photoexcitation conditions, charges and holes migrate efficiently along the curved band and internal electric field, further enhancing charge-hole separation. As a result, the removal capacity of CoWO4/TpDD increases from 515.2 mg/g in the dark to 1754.6 mg/g under light conditions. Thus, constructing a p-n heterojunction proves to be an effective strategy for remediating uranium-contaminated environments.

Well-Tailored Norbornene-Based Fluorinated Copolymers toward Modulating Icephobicity and Mechanical Robustness.

Well-tailored construction of icephobic surfaces with mechanical robustness and investigation of the structure-property relationships at the molecular level are highly desirable. Herein, a series of norbornene-based fluorinated polyolefin copolymers (FPOR-x) with varying norbornenyl dodecafluoroheptyl ester (NDFHE) molar fractions (0-100 mol %) were well-designed and fabricated via living ring-opening metathesis polymerization (ROMP) employing NDFHE and norbornenyl pentafluorophenyl ester (NPFPE) as the soft and hard segments, respectively. The mechanical and icephobic properties of the fluorinated copolymers can be regulated by adjusting the soft NDFHE contents. As a result, the well-designed norbornene-based copolymers exhibited a wide range of tunable mechanical properties, including tensile strength ranging from 0.2 to 26.4 MPa, elastic modulus ranging from 0.6 to 593.7 MPa, and breaking elongations ranging from 5718.7% to 3.7%, correlating with the proportion of soft NDFHE content. Furthermore, the synergistic interplay between soft and hard segments, particularly the hardness in the majority and softness in the minority or vice versa, could achieve a significant difference in the local modulus and enhance the propagations of cracks within the three-phase regions (soft regions/hard regions/ice), ultimately leading to a significant reduction in ice shear strength. Notably, FPOR-25% with a tensile strength of 12.0 MPa and an elastic modulus of 227.5 MPa exhibited a remarkably low ice shear strength of 57.7 kPa. This study not only highlights the relationship between the polymer molecular structure and surface icephobic properties but also breaks the limitations of icephobic surfaces with a low modulus.

Wormlike micellar solutions formed by an anionic surfactant and a cationic surfactant with two head groups.

Innovation in the molecular structure of surfactants is important for the preparation of soft materials with novel properties. In this study, we synthesized a cationic surfactant, N1,N1,N1,N1,N3,N3,N3-pentamethyl-N3-(3-stearamidopropyl)propane-1,3-diammonium bromide, hereafter referred to as C18-DQA. Unlike conventional cationic surfactants, C18-DQA contains two quaternary ammonium head groups and a long-saturated alkyl chain equal to a chain length of 21 carbon atoms. C18-DQA exhibits a low Krafft point of ∼0 °C and a water solubility >1000 mM at 25 °C. The critical micelle concentration (cmc) of C18-DQA was determined to be 0.59 mM using the Nile red method. C18-DQA was mixed with sodium laurate (SL) at different molar ratios to produce transparent solutions with excellent viscoelasticity over a wide concentration range. The 1 : 1.5 molar ratio C18-DQA/SL mixed solutions exhibited gel-like behavior for a total surfactant concentration of 2.88 wt% (75 mM). The solution with a total surfactant concentration of 300 mM (120 mM C18-DQA and 180 mM SL) achieved a maximum zero-shear viscosity (η0) of 4224 Pa s. Cryogenic transmission electron microscopy analysis revealed the formation of extremely long wormlike micelles, with a cross-sectional diameter of 5 nm and contour length >3 µm, in the mixed solutions. C18-DQA and SL molecules were drawn close by electrostatic attractions, leading to a suitable molecular geometry for the extensive growth of wormlike micelles. This work will act as an important reference for the future preparation of highly viscoelastic solutions by mixing cationic and anionic surfactants. The proposed system is also expected to have potential applications in cosmetic formulations, home care products, and oilfield fracturing fluids.

Efficacy of Chinese herbal formula Kai-Xin-San on rodent models of depression: A systematic review and meta-analysis.

ETHNOPHARMACOLOGICAL RELEVANCE: Kai-Xin-San (KXS, or Happy Feeling Powder), a typical Chinese herbal prescription, is frequently used for treating depression by the multi-level and multi-target mechanism. AIM OF THE STUDY: To systematically investigate the efficacy and safety of KXS on depression in preclinic trials. MATERIALS AND METHODS: We independently searched for preclinical animal studies of KXS on depression from inception to June 28, 2022, using electronic databases, e.g., PUBMED. The measurements were performed to assess the outcomes of behavioral tests. RESULTS: This systematic review and meta-analysis included twenty-four studies and 608 animals. A remarkable effect of KXS in depression behavioral tests, including sucrose consumption test (SMD: 2.36, 95% CI: (1.81, 2.90); Z = 8.49, P < 0.00001)., forced swimming test (MD = -60.52, 95% CI: (-89.04, -31.99); Z = 4.16, P < 0.0001), rearing times (MD=4.48, 95% CI: (3.39, 5.57); Z = 8.05, P < 0.00001) and crossing times (MD = -33.7, 95% CI: (25.74, 41.67); Z = 8.29, P < 0.00001) in the open field test, showing KXS's excellent efficiency in improving depressive-like symptoms of animals. CONCLUSIONS: Our meta-analysis showed KXS remarkably relieved animals' depressive-like symptoms, providing evidence that KXS can be a promising drug candidate for depression treatment.

A systematic review and meta-analysis of the efficacy of ketamine and esketamine on suicidal ideation in treatment-resistant depression.

PURPOSE: To systematically assess the evidence of efficacy and safety of the use of ketamine and esketamine for patients with treatment-resistant depression (TRD) with suicidal ideation (SI). METHODS: We independently searched for clinical trials from inception to January 2023 using electronic databases, e.g., PubMed and EMBASE. A systematic review and meta-analysis were performed to assess SI scores of depression rating scales, which were regarded as the outcomes. RESULTS: A total of five independent double-blind, placebo controlled randomized clinical trials (RCTs) are eligible for inclusion. Four of the studies used ketamine as an intervention and one used esketamine as an intervention. Three hundred ninety-one patients with TRD were included (the intervention group with ketamine or esketamine is 246, and the control group is 145). No statistically significant interaction between the subscales of suicide ideation (SMD = - 0.66, 95% CI (- 1.61, 0.29); Z = 1.36, P = 0.17) and antidepressant effects (SMD = - 0.99, 95% CI (- 2.33, 0.34); Z = 1.46, P = 0.15) based on the results of ketamine and esketamine, compared with placebo groups. CONCLUSION: This meta-analysis suggested that esketamine and ketamine have failed to reduce suicidal ideation in patients with TRD. Further studies are desirable to confirm the effects of ketamine and esketamine in TRD patients.

Astroglial Connexin 43-Mediated Gap Junctions and Hemichannels: Potential Antidepressant Mechanisms and the Link to Neuroinflammation.

Major depression disorder (MDD) is a neuropsychiatric disorder associated with a high suicide rate and a higher disability rate than any other disease. Evidence suggests that the pathological mechanism of MDD is related to astrocyte dysfunction. Depression is mainly associated with the expression of connexin 43 (Cx43) and the function of Cx43-mediated gap junctions and hemichannels in astrocytes. Moreover, neuroinflammation has been a hotspot in research on the pathology of depression, and Cx43-mediated functions are thought to be involved in neuroinflammation-related depression. However, the specific mechanism of Cx43-mediated functions in neuroinflammation-related depression pathology remains unclear. Therefore, this review summarizes and discusses Cx43 expression, the role of gap junction intercellular communication, and its relationship with neuroinflammation in depression. This review also focuses on the effects of antidepressant drugs (e.g., monoamine antidepressants, psychotropic drugs, and N-methyl-D-aspartate receptor antagonists) on Cx43-mediated function and provides evidence for Cx43 as a novel target for the treatment of MDD. The pathogenesis of MDD is related to astrocyte dysfunction, with reduced Cx43 expression, GJ dysfunction, decreased GJIC and reduced BDNF expression in the depressed brain. The effect of Cx43 on neuroinflammation-related depression involving inflammatory cytokines, glutamate excitotoxicity, and HPA axis dysregulation. Antidepressant drugs targeting Cx43 can effectively relieve depressive symptoms.

Urine based near-infrared spectroscopy analysis reveals a noninvasive and convenient diagnosis method for cancers: a pilot study.

Background: The challenges in cancer diagnosis underline the need for continued research and development of new diagnostic tools and methods. This study aims to explore an effective, noninvasive, and convenient diagnostic tool using urine based near-infrared spectroscopy (NIRS) analysis combined with machine learning algorithm. Methods: Urine samples were collected from a total of 327 participants, including 181 cancer cases and 146 healthy controls. These participants were randomly spit into train set (n = 218) and test set (n = 109). NIRS analysis (4,000 ∼10,000 cm-1) was performed for each sample in both train and test sets. Five pretreatment methods, including Savitzky-Golay (SG) smoothing, multiplicative scatter correction (MSC), baseline removal (BSL) with fitting polynomials to be used as baselines, the first derivative (DERIV1), and the second derivative (DERIV2), and combination with "scaling" and "center", were investigated. Then partial least-squares (PLS) and linear support-vector machine (SVM) classification models were established, and prediction performance was evaluated in test set. Results: NIRS had greatly overlapping in peaks, and PCA analysis failed in separation between cancers and healthy controls. In modeling with urine based NIRS data, PLS model showed its highest prediction accuracy of 0.780, with DERIV2, "scaling" and "center" pretreatment, while linear SVM displayed its best prediction accuracy of 0.844, with raw NIRS. With optimization in SVM, the prediction accuracy could improve to 0.862, when the top 262 features were involved as variables. Discussion: This pilot study combining urine based NIRS analysis and machine learning is effective and convenient that might facilitate in cancer diagnosis, encouraging further evaluation with a large-size multi-center study.

Synergistic effect of double Schottky potential well and oxygen vacancy for enhanced plasmonic photocatalytic U(VI) reduction.

Plasmonic photocatalysis is an effective strategy to solve radioactive uranium hazards in wastewater. A plasmonic photocatalyst Bi/Bi2O3-x@COFs was synthesized by in-situ growth of covalent organic frameworks (COFs) on Bi/Bi2O3-x surface for the U(VI) adsorption and plasmonic photoreduction in rare earth tailings wastewater. The presence of oxygen vacancy in Bi/Bi2O3-x and Schottky potential well formed by Bi and Bi2O3-x interface increased the number of free electrons, which induced localized surface plasmon resonance (LSPR) and enhanced the light absorption performance of composites. In addition, oxygen vacancy improved the Fermi level of Bi/Bi2O3-x, leading to another potential well between Bi2O3-x and COFs interface. The electron transport direction was reversed, thus increasing the electron density of COFs layer. COFs was an N-type semiconductor with specific binding U(VI) groups and suitable band structure, which could be used as an active reaction site. Bi/Bi2O3-x@COFs had 1411.5 mg g-1 removal capacity and high separation coefficient for U(VI) due to the synergistic action of photogenerated electrons and hot electrons. Moreover, the removal rate of uranium from rare earth tailings wastewater by regenerated Bi/Bi2O3-x@COFs was over 93.9%. The scheme of introducing LSPR and Schottky potential well provides another way to improve the photocatalytic effect.

SGRT-based DIBH radiotherapy practice for right-sided breast cancer combined with RNI: A retrospective study on dosimetry and setup accuracy.

BACKGROUND: We retrospectively studied the dosimetry and setup accuracy of deep inspiration breath-hold (DIBH) radiotherapy in right-sided breast cancer patients with regional nodal irradiation (RNI) who had completed treatment based on surface-guided radiotherapy (SGRT) technology by Sentinel/Catalyst system, aiming to clarify the clinical application value and related issues. METHODS: Dosimetric indicators of four organs at risk (OARs), namely the heart, right coronary artery (RCA), right lung, and liver, were compared on the premise that the planning target volume met dose-volume prescription requirements. Meanwhile, the patients were divided into the edge of the xiphoid process (EXP), sternum middle (SM), and left breast wall (LBW) groups according to different positions of respiratory gating primary points. The CBCT setup error data of the three groups were contrasted for the treatment accuracy study, and the effects of different gating window heights on the right lung volume increases were compared among the three groups. RESULTS: Compared with free breath (FB), DIBH reduced the maximum dose of heart and RCA by 739.3 ± 571.2 cGy and 509.8 ± 403.8 cGy, respectively (p < 0.05). The liver changed the most in terms of the mean dose (916.9 ± 318.9 cGy to 281.2 ± 150.3 cGy, p < 0.05). The setup error of the EXP group in the anterior-posterior (AP) direction was 3.6 ± 4.5 mm, which is the highest among the three groups. The right lung volume increases in the EXP, SM, and LBW groups were 72.3%, 69.9%, and 67.2%, respectively (p = 0.08), and the corresponding breath-holding heights were 13.5 ± 3.7 mm, 10.3 ± 2.4 mm, and 9.6 ± 2.8 mm, respectively (p < 0.05). CONCLUSIONS: SGRT-based DIBH radiotherapy can better protect the four OARs of right-sided breast cancer patients with RNI. Different respiratory gating primary points have different setup accuracy and breath-hold height.

Antidepressant effects of the traditional Chinese herbal formula Xiao-Yao-San and its bioactive ingredients.

BACKGROUND: Depression is one of the most debilitating and severe psychiatric disorders and a serious public health concern. Currently, many treatments are indicated for depression, including traditional Chinese medicinal formulae such as Xiao-Yao-San (XYS), which has effective antidepressant effects in clinical and animal studies. PURPOSE: To summarize current evidence of XYS in terms of the preclinical and clinical studies and to identify the multi-level, multi-approach, and multi-target potential antidepressant mechanisms of XYS and active components of XYS by a comprehensive search of the related electronic databases. METHODS: The following electronic databases were searched from the beginning to April 2022: PubMed, MEDLINE, Web of Science, Google Scholar, and China National Knowledge Infrastructure. RESULTS: This review summarizes the antidepressant mechanisms of XYS and its active ingredients, which are reportedly correlated with monoamine neurotransmitter regulation, synaptic plasticity, and hypothalamic-pituitary-adrenal axis, etc. CONCLUSION: XYS plays a critical role in the treatment of depression by the regulation of several factors, including the monoaminergic systems, hypothalamic-pituitary-adrenal axis, synaptic plasticity, inflammation, brain-derived neurotrophic factor levels, brain-gut axis, and other pathways. However, more clinical and animal studies should be conducted to further investigate the antidepressant function of XYS and provide more evidence and recommendations for its clinical application. Our review provides an overview of XYS and guidance for future research direction.

Prediction model for knee osteoarthritis using magnetic resonance-based radiomic features from the infrapatellar fat pad: data from the osteoarthritis initiative.

Background: The infrapatellar fat pad (IPFP) plays an important role in the incidence of knee osteoarthritis (OA). Magnetic resonance (MR) signal heterogeneity of the IPFP is related to pathologic changes. In this study, we aimed to investigate whether the IPFP radiomic features have predictive value for incident radiographic knee OA (iROA) 1 year prior to iROA diagnosis. Methods: Data used in this work were obtained from the osteoarthritis initiative (OAI). In this study, iROA was defined as a knee with a baseline Kellgren-Lawrence grade (KLG) of 0 or 1 that further progressed to KLG ≥2 during the follow-up visit. Intermediate-weighted turbo spin-echo knee MR images at the time of iROA diagnosis and 1 year prior were obtained. Five clinical characteristics-age, sex, body mass index, knee injury history, and knee surgery history-were obtained. A total of 604 knees were selected and matched (302 cases and 302 controls). A U-Net segmentation model was independently trained to automatically segment the IPFP. The prediction models were established in the training set (60%). Three main models were generated using (I) clinical characteristics; (II) radiomic features; (III) combined (clinical plus radiomic) features. Model performance was evaluated in an independent testing set (remaining 40%) using the area under the curve (AUC). Two secondary models were also generated using Hoffa-synovitis scores and clinical characteristics. Results: The comparison between the automated and manual segmentations of the IPFP achieved a Dice coefficient of 0.900 (95% CI: 0.891-0.908), which was comparable to that of experienced radiologists. The radiomic features model and the combined model yielded superior AUCs of 0.700 (95% CI: 0.630-0.763) and 0.702 (95% CI: 0.635-0.763), respectively. The DeLong test found no statistically significant difference between the receiver operating curves of the radiomic and combined models (P=0.831); however, both models outperformed the clinical model (P=0.014 and 0.004, respectively). Conclusions: Our results demonstrated that radiomic features of the IPFP are predictive of iROA 1 year prior to the diagnosis, suggesting that IPFP radiomic features can serve as an early quantitative prediction biomarker of iROA.

Two fully automated data-driven 3D whole-breast segmentation strategies in MRI for MR-based breast density using image registration and U-Net with a focus on reproducibility.

Presence of higher breast density (BD) and persistence over time are risk factors for breast cancer. A quantitatively accurate and highly reproducible BD measure that relies on precise and reproducible whole-breast segmentation is desirable. In this study, we aimed to develop a highly reproducible and accurate whole-breast segmentation algorithm for the generation of reproducible BD measures. Three datasets of volunteers from two clinical trials were included. Breast MR images were acquired on 3 T Siemens Biograph mMR, Prisma, and Skyra using 3D Cartesian six-echo GRE sequences with a fat-water separation technique. Two whole-breast segmentation strategies, utilizing image registration and 3D U-Net, were developed. Manual segmentation was performed. A task-based analysis was performed: a previously developed MR-based BD measure, MagDensity, was calculated and assessed using automated and manual segmentation. The mean squared error (MSE) and intraclass correlation coefficient (ICC) between MagDensity were evaluated using the manual segmentation as a reference. The test-retest reproducibility of MagDensity derived from different breast segmentation methods was assessed using the difference between the test and retest measures (Δ2-1), MSE, and ICC. The results showed that MagDensity derived by the registration and deep learning segmentation methods exhibited high concordance with manual segmentation, with ICCs of 0.986 (95%CI: 0.974-0.993) and 0.983 (95%CI: 0.961-0.992), respectively. For test-retest analysis, MagDensity derived using the registration algorithm achieved the smallest MSE of 0.370 and highest ICC of 0.993 (95%CI: 0.982-0.997) when compared to other segmentation methods. In conclusion, the proposed registration and deep learning whole-breast segmentation methods are accurate and reliable for estimating BD. Both methods outperformed a previously developed algorithm and manual segmentation in the test-retest assessment, with the registration exhibiting superior performance for highly reproducible BD measurements.

Platelet-to-Portal Vein Width Ratio and Platelet-to-Spleen Thickness Ratio Can Be Used to Predict Progressive Liver Fibrosis Among Patients With HBV Infection With HBeAg-Negativity and a Normal ALT Level.

Background: Some people infected with the hepatitis B virus (HBV) with a normal level of alanine aminotransferase (ALT) are at risk of disease progression. We evaluated the value of platelet-to-portal vein width ratio (PPR) and platelet-to-spleen thickness ratio (PSR) to predict progressive liver fibrosis among patients with HBV infection with HBV e antigen (HBeAg)-negativity and a normal ALT level. Methods: HBV surface antigen (HBsAg)-positive and HBeAg-negative individuals with a normal ALT level were enrolled. The inflammation grade (G) and fibrosis stage(S) were analyzed according to pathological features. Then, two groups ( 0.05). The platelet count, PPR, and PSR were significantly different between the two groups [(145.92 ± 14.55) ×109/L vs. (126.38 ± 23.85) ×109/L, p = 0.008; 10.80 ± 1.30 vs. 9.01 ± 1.97, p = 0.004; 4.21 ± 0.65 vs. 3.33 ± 0.89, p = 0.02, respectively]. The PPR and PSR decreased gradually upon fibrosis aggravation (p < 0.05). Based on the cut off value of the PPR (9.07) and PSR (3.54), their sensitivity and specificity was 0.917 and 0.525, and 0.833 and 0.541, respectively. Conclusion: The PPR and PSR can be employed to assess earlier fibrosis progression among patients with HBV infection with HBeAg-negativity and a normal ALT level.

Preoperative prediction of lymph node metastasis using deep learning-based features.

Lymph node involvement increases the risk of breast cancer recurrence. An accurate non-invasive assessment of nodal involvement is valuable in cancer staging, surgical risk, and cost savings. Radiomics has been proposed to pre-operatively predict sentinel lymph node (SLN) status; however, radiomic models are known to be sensitive to acquisition parameters. The purpose of this study was to develop a prediction model for preoperative prediction of SLN metastasis using deep learning-based (DLB) features and compare its predictive performance to state-of-the-art radiomics. Specifically, this study aimed to compare the generalizability of radiomics vs DLB features in an independent test set with dissimilar resolution. Dynamic contrast-enhancement images from 198 patients (67 positive SLNs) were used in this study. Of these subjects, 163 had an in-plane resolution of 0.7 × 0.7 mm2, which were randomly divided into a training set (approximately 67%) and a validation set (approximately 33%). The remaining 35 subjects with a different in-plane resolution (0.78 × 0.78 mm2) were treated as independent testing set for generalizability. Two methods were employed: (1) conventional radiomics (CR), and (2) DLB features which replaced hand-curated features with pre-trained VGG-16 features. The threshold determined using the training set was applied to the independent validation and testing dataset. Same feature reduction, feature selection, model creation procedures were used for both approaches. In the validation set (same resolution as training), the DLB model outperformed the CR model (accuracy 83% vs 80%). Furthermore, in the independent testing set of the dissimilar resolution, the DLB model performed markedly better than the CR model (accuracy 77% vs 71%). The predictive performance of the DLB model outperformed the CR model for this task. More interestingly, these improvements were seen particularly in the independent testing set of dissimilar resolution. This could indicate that DLB features can ultimately result in a more generalizable model.