Background:Chest computed tomography (CT) seldom covers the third lumbar (L3) vertebral level, the standard landmark for assessing total body muscle mass. As muscle measurements at the fourth thoracic (T4) level show high concordance with those at L3, the T4 level may serve as a viable alternative. We evaluated the discriminatory performance of T4 musculature for lung cancer-related low thoracic muscle mass (LTMM) and its association with Eastern Cooperative Oncology Group (ECOG) performance status. Methods:We retrospectively included 289 inpatients with newly diagnosed lung cancer who underwent chest CT within 3 months. At T4, the pectoralis major, pectoralis minor, and chest-wall muscle group were segmented to derive cross-sectional area (CSA), density, and height-normalized indices (cm2/m2). Low thoracic muscle mass (LTMM) was defined by sex-specific 25th-percentile thoracic 4th vertebra level muscle index (T4MI) cutoffs (40.78 cm2/m2 for men, 33.15 cm2/m2 for women). Patients were stratified by sex and clinical stage (I-II early-stage vs. III-IV advanced-stage). ROC analyses compared discriminatory performance; logistic regression tested associations with poor ECOG performance status. Results:Compared with non-low thoracic muscle mass (non-LTMM), low thoracic muscle mass (LTMM) group showed smaller CSA, lower density, and reduced indices. Across muscle groups, indices outperformed CSA and density. The pectoralis major index achieved the highest AUC in the overall cohort (AUC = 0.833) and reached excellent discrimination in the overall male cohort (AUC = 0.922). Notably, stage-stratified analyses showed consistently superior discriminatory performance for the pectoralis major index in the male population (early-stage AUC = 0.917, advanced-stage AUC = 0.912). In addition, the pectoralis major index was independently associated with poor ECOG performance status (odds ratio = 0.932, p = 0.009). Conclusion:T4-level muscle metrics showed good internal discrimination for lung cancer-related low thoracic muscle mass across sex and disease stage, with the pectoralis major index achieving the highest overall performance. Moreover, the pectoralis major index may be a potential imaging biomarker associated with ECOG performance status.

INTRODUCTION:Acute leukemia harboring rearrangement of the Mixed lineage leukemia (MLL) and/or mutation of the nucleophosmin is a type of poorly prognostic and highly malignant leukemia which is extremely difficult to treat. Blocking the protein-protein interaction between Menin and MLL is a strategic approach for treating leukemias, as a new direction for drug discovery. Many biotech and pharmaceutical companies made great efforts to this drug development field, and a large number of small molecular Menin-MLL PPI inhibitors were reported during the recent three years. AREAS COVERED:This review is to mainly summarize the Menin-MLL PPI inhibitors reported in the recent three years' patents. EXPERT OPINION:Although the past 12 years have witnessed the progress of the Menin-MLL PPI inhibitors in the treatment of acute leukemia, especially for leukemia harboring rearranged KMT2A and/or mutated NPM1, recent studies showed Menin-MLL PPI inhibitors suffered from new issues such as toxicity, acquired resistance, and homogenization. Therefore, new drug discovery strategies should be considered in advance. The expert opinion was proposed from several aspects, such as developing diverse chemical structures, discovering covalent inhibitors, designing small molecular PROTACs, and targeting the amino acids mutations for next-generation inhibitors.

Polydopamine (PDA) as a versatile coating material has attracted broad interest in the application of electroless deposition (ELD) due to its facile fabrication and abundant resources. The cross-linking density of PDA has an important effect on surface binding properties. Due to the complexity of cross-linked networks, however, it is still difficult to directly detect the cross-linking degree of polymers at a microscopic level. In this study, PDA coatings are measured at the single-molecule level by means of atomic force microscopy (AFM)-based single-molecule force spectroscopy (SMFS). The obtained single peak (S-type) and multiple peak (M-type) force curves are used to define the typical force-extension (F-E) curves of the linear polymers with single chain and the cross-linked polymers with multiple chains, respectively. Furthermore, the as-prepared Cu plating PDA deposited PP substrate also exhibits excellent metallic conductivity in the deposition of DA for 16 h at the concentration of 0.02 M, which is in accordance with those from the SMFS results. Attributed to the scanning electron microscopy (SEM), fourier transform infrared spectrum (FTIR) and some other measurements, it further indicates that PDA with different cross-linking degrees using SMFS has proven the role as both reductive sites and binder in the ELD of Cu on polymer substrate. Besides, it is expected that AFM-based SMFS can be used as a general method to study different cross-linked polymers in the ELD and other surface modification processes.

Owing to advances in diagnosis and treatment methods over past decades, a growing number of early-stage hepatocellular carcinoma (HCC) diagnoses has enabled a greater of proportion of patients to receive curative treatment. However, a high risk of early recurrence and poor prognosis remain major challenges in HCC therapy. Microvascular invasion (MVI) has been demonstrated to be an essential independent predictor of early recurrence after curative therapy. Currently, biopsy is not generally recommended before treatment to evaluate MVI in HCC according clinical guidelines due to sampling error and the high risk of tumor cell seeding following biopsy. Therefore, the postoperative histopathological examination is recognized as the gold standard of MVI diagnosis, but this lagging indicator greatly impedes clinicians in selecting the optimal effective treatment for prognosis. As imaging can now noninvasively and completely assess the whole tumor and host situation, it is playing an increasingly important role in the preoperative assessment of MVI. Therefore, imaging criteria for MVI diagnosis would be highly desirable for optimizing individualized therapeutic decision-making and achieving a better prognosis. In this review, we summarize the emerging image characteristics of different imaging modalities for predicting MVI. We also discuss whether advances in imaging technique have generated evidence that could be practice-changing and whether advanced imaging techniques will revolutionize therapeutic decision-making of early-stage HCC.

Abstract Background Neurological complications are a significant concern of Coronavirus Disease 2019 (COVID-19). However, the pathogenic mechanism of neurological symptoms associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is poorly understood. Methods We used Drosophila as a model to systematically analyze SARS-CoV-2 genes encoding structural and accessory proteins and identified the membrane protein (M) that disrupted mitochondrial functions in vivo. The M protein was stereotaxically injected to further assess its effects in the brains of wild-type (WT) and 5 × FAD mice. Omics technologies, including RNA sequencing and interactome analysis, were performed to explore the mechanisms of the effects of M protein both in vitro and in vivo. Results Systematic analysis of SARS-CoV-2 structural and accessory proteins in Drosophila identified that the M protein induces mitochondrial fragmentation and dysfunction, leading to reduced ATP production, ROS overproduction, and eventually cell death in the indirect flight muscles. In WT mice, M caused hippocampal atrophy, neural apoptosis, glial activation, and mitochondrial damage. These changes were further aggravated in 5 × FAD mice. M was localized to the Golgi apparatus and genetically interacted with four wheel drive (FWD, a Drosophila homolog of mammalian PI4KIIIβ) to regulate Golgi functions in flies. Fwd RNAi, but not PI4KIIIα RNAi, reversed the M-induced Golgi abnormality, mitochondrial fragmentation, and ATP reduction. Inhibition of PI4KIIIβ activity suppressed the M-induced neuronal cell death. Therefore, M induced mitochondrial fragmentation and apoptosis likely through disruption of Golgi-derived PI(4)P-containing vesicles. Conclusions M disturbs the distribution and function of Golgi, leading to mitochondrial abnormality and eventually neurodegeneration via a PI4KIIIβ-mediated mechanism. This study reveals a potential mechanism for COVID-19 neurological symptoms and opens a new avenue for development of therapeutic strategies targeting SARS-CoV-2 M or mitochondria.

In this paper, an image construction algorithm was applied to detect the defects within the experimental aluminum block in the field of non-destructive inspection, which was always called total focusing method. Before applying this kind of TFM, an advanced data acquisition method whose name was full matrix capture was implemented to get time domain ultrasonic signal set. Besides, some preprocessing techniques was carried out before using TFM, such as Fourier Transform and Hilbert Transform. Finally, various kinds of results with different preprocessing methods were demonstrated at the end of this paper.

Abstract Objective Due to inconsistency in neoadjuvant chemotherapy (NACT) response in advanced gastric cancer (GC), the indications remain the source of controversy. This study focused on identifying factors related to NACT chemosensitivity and providing the best treatment for GC cases. Methods Clinical data in 867 GC cases treated with neoadjuvant chemotherapy were downloaded from two medical centers between January 2014 and December 2020, and analyzed by logistic regression and the least absolute shrinkage and selection operator (LASSO) for identifying potential factors that predicted NACT response and might be incorporated in constructing the prediction nomogram. Results After the inclusion and exclusion criteria were applied, totally 460 cases were enrolled, among which, 307 were males (66.74%) whereas 153 were females (33.26%), with the age of 24–77 (average, 59.37 ± 10.60) years. Consistent with RECIST standard, 242 patients were classified into effective group (PR or CR) while 218 were into ineffective group (PD or SD), with the effective rate of 52.61%. In training set, LASSO and logistic regression analysis showed that five risk factors were significantly associated with NACT effectiveness, including tumor location, Smoking history, T and N stages, and differentiation. In terms of our prediction model, its C-index was 0.842. Moreover, calibration curve showed that the model-predicted results were in good consistence with actual results. Validation based on internal and external validation sets exhibited consistency between training set results and ours. Conclusions This study identified five risk factors which were significantly associated with NACT response, including smoking history, clinical T stage, clinical N stage, tumor location and differentiation. The prediction model that exhibited satisfying ability to predict NACT effectiveness was constructed, which may be adopted for identifying the best therapeutic strategy for advanced GC by gastrointestinal surgeons.

Alzheimer's disease (AD) is an age-related neurodegenerative disease that is primary characterized as a cognitive disorder. Its pathology is characterized by the formation of senile plaques in the brain from amyloid-beta (Aβ) aggregation, neuronal fibrillary tangles from hyperphosphorylated tau protein aggregation, prolonged inflammatory responses, and neuronal death. The pathogenesis and clinical manifestations of AD are complex, but aging is generally accepted as one of the most important contributing factors. In addition, there are several hypotheses, including the Aβ hypothesis based on amyloid plaques, the tau hypothesis based on neuronal fiber entanglement, the inflammation hypothesis based on long-term inflammatory responses causing brain damage, and the neuroprotection hypothesis based on synaptic dysfunction and neuronal death. Although the pathogenesis of AD has been broadly classified into four major hypotheses, there are multiple forms of interactions, which is one of the reasons for its complex pathogenesis. Numerous epidemiological studies have shown the important role of genes in AD, followed by brain damage, hyperlipidemia, diabetes, hypertension, and obesity as risk factors for the disease. Despite years of research, several mysteries in AD remain unsolved. Drugs based on various pathogenetic hypotheses are being investigated in large numbers, but the effects are unsatisfactory. In recent years, traditional Chinese medicine (TCM) has made excellent progress and is expected to provide a new possibility for AD treatment. In this review, we focus on the latest developments in studies on the risk factors-Aβ aggregates and related factors such as apolipoprotein E, synaptic loss, and fatty acids, and then present the progress in the research of TCM based on the above pathogenesis, intended to provide a research reference and treatment for AD.

Patients with type 2 diabetes mellitus (T2DM) often have cognitive impairment and structural brain abnormalities. The magnetic resonance imaging (MRI)-based brain atrophy and lesion index can be used to evaluate common brain changes and their correlation with cognitive function, and can therefore also be used to reflect whole-brain structural changes related to T2DM. A total of 136 participants (64 men and 72 women, aged 55-86 years) were recruited for our study between January 2014 and December 2016. All participants underwent MRI and Mini-Mental State Examination assessment (including 42 healthy control, 38 T2DM without cognitive impairment, 26 with cognitive impairment but without T2DM, and 30 T2DM with cognitive impairment participants). The total and sub-category brain atrophy and lesion index scores in patients with T2DM with cognitive impairment were higher than those in healthy controls. Differences in the brain atrophy and lesion index of gray matter lesions and subcortical dilated perivascular spaces were found between non-T2DM patients with cognitive impairment and patients with T2DM and cognitive impairment. After adjusting for age, the brain atrophy and lesion index retained its capacity to identify patients with T2DM with cognitive impairment. These findings suggest that the brain atrophy and lesion index, based on T1-weighted and T2-weighted imaging, is of clinical value for identifying patients with T2DM and cognitive impairment. Gray matter lesions and subcortical dilated perivascular spaces may be potential diagnostic markers of T2DM that is complicated by cognitive impairment. This study was approved by the Medical Ethics Committee of University of South China (approval No. USC20131109003) on November 9, 2013, and was retrospectively registered with the Chinese Clinical Trial Registry (registration No. ChiCTR1900024150) on June 27, 2019.

INTRODUCTION:Chromosomal translocations involving the mixed-lineage leukemia (MLL, KMT2A, MLL1) genes result in the production of MLL fusion proteins, which cause abnormal transcriptional regulation leading to acute leukemia (AL). Menin (MEN1) protein is essential for MLL to regulate the expression of related target genes. High-affinity interactions between the amino terminus of MLL proteins and Menin proteins are required to mediate the oncogenic transformation of MLL fusion proteins. Therefore, inhibition of Menin and MLL interaction is a potential therapeutic strategy for MLL rearrangement (MLL-r) leukemia and can provide a new choice for treatment of other diseases. Therefore, researchers have made great efforts to explore small-molecule Menin-MLL interaction inhibitors.AREAS COVERED:This review is to provide an overview of the patented Menin-MLL protein-protein interaction inhibitors from 2014 to 2021.EXPERT OPINION:Menin-MLL interaction inhibitors have therapeutic potential in the treatment of acute leukemia, such as AML and ALL. SNDX-5613 and KO-539 have been granted orphan drug designation by the FDA for treatment of refractory/relapsed leukemia and AML, respectively. In addition, they are undergoing clinical evaluation for other indications. It is clear that Menin-MLL interaction inhibitors have promising benefits in the clinical treatment of leukemia and other diseases.

Texture analysis is an emerging field that allows mathematical detection of changes in MRI signals that are not visible among image pixels. Alzheimer's disease, a progressive neurodegenerative disease, is the most common cause of dementia. Recently, multiple texture analysis studies in patients with Alzheimer's disease have been performed. This review summarizes the main contributors to Alzheimer's disease-associated cognitive decline, presents a brief overview of texture analysis, followed by review of various MR imaging texture analysis applications in Alzheimer's disease. We also discuss the current challenges for widespread clinical utilization. MR texture analysis could potentially be applied to develop neuroimaging biomarkers for use in Alzheimer's disease clinical trials and diagnosis.

ObjectiveTo seek optimal keV settings for imaging carpal tunnel in adults by dual-energy computed tomography (DECT) monoenergetic technique; to describe anatomic characteristics of carpal tunnel and to observe correlation between carpal bony and soft tissue structures.METHODSDECT images of 20 wrists (11 left and 9 right wrists; 14 men, mean age 26.93±1.38 years, range 23 to 28, and 6 women, mean age 24.17 ± 0.98 years, range 23 to 26) were evaluated. Monoenergetic images were reconstructed at 42, 62, 82, 102, 122, and 142 keV. Image quality was assessed along a 5-point Likert scale, and the highest-quality images were chosen for quantitative analysis. Two musculoskeletal radiologists performed both analyses independently.RESULTSThe optimal energy spectrum with the best contrast-to-noise ratio (CNR) for monoenergetic images were at 62 keV (19 wrists, 95%) and 61 keV (1 wrist, 5%). There was substantial interobserver agreement between the readers in the 5-point Likert scale analysis of image quality (k= 0.793). Bland-Altman plots also indicated good agreement between observers in quantitative analysis. Intra-category 1 and 2 correlation was mostly discovered at hamate hook level and middle level of pisiform (P < 0.05), while bony and soft tissue structures partly reached correlation (P < 0.05).CONCLUSIONSThe optimal energy spectrum for monoenergetic DECT imaging of carpal tunnel structures was 62 keV. DECT monoenergetic imaging could predict changes in soft tissue structures and demonstrate carpal tunnel anatomic structures.