Cross-Modality Reference and Feature Mutual-Projection for 3D Brain MRI Image Super-Resolution.

High-resolution (HR) magnetic resonance imaging (MRI) can reveal rich anatomical structures for clinical diagnoses. However, due to hardware and signal-to-noise ratio limitations, MRI images are often collected with low resolution (LR) which is not conducive to diagnosing and analyzing clinical diseases. Recently, deep learning super-resolution (SR) methods have demonstrated great potential in enhancing the resolution of MRI images; however, most of them did not take the cross-modality and internal priors of MR seriously, which hinders the SR performance. In this paper, we propose a cross-modality reference and feature mutual-projection (CRFM) method to enhance the spatial resolution of brain MRI images. Specifically, we feed the gradients of HR MRI images from referenced imaging modality into the SR network to transform true clear textures to LR feature maps. Meanwhile, we design a plug-in feature mutual-projection (FMP) method to capture the cross-scale dependency and cross-modality similarity details of MRI images. Finally, we fuse all feature maps with parallel attentions to produce and refine the HR features adaptively. Extensive experiments on MRI images in the image domain and k-space show that our CRFM method outperforms existing state-of-the-art MRI SR methods.

Machine learning-Based model for prediction of Narcolepsy Type 1 in Patients with Obstructive Sleep Apnea with Excessive Daytime Sleepiness.

Background: Excessive daytime sleepiness (EDS) forms a prevalent symptom of obstructive sleep apnea (OSA) and narcolepsy type 1 (NT1), while the latter might always be overlooked. Machine learning (ML) models can enable the early detection of these conditions, which has never been applied for diagnosis of NT1. Objective: The study aimed to develop ML prediction models to help non-sleep specialist clinicians identify high probability of comorbid NT1 in patients with OSA early. Methods: Totally, clinical features of 246 patients with OSA in three sleep centers were collected and analyzed for the development of nine ML models. LASSO regression was used for feature selection. Various metrics such as the area under the receiver operating curve (AUC), calibration curve, and decision curve analysis (DCA) were employed to evaluate and compare the performance of these ML models. Model interpretability was demonstrated by Shapley Additive explanations (SHAP). Results: Based on the analysis of AUC, DCA, and calibration curves, the Gradient Boosting Machine (GBM) model demonstrated superior performance compared to other machine learning (ML) models. The top five features used in the GBM model, ranked by feature importance, were age of onset, total limb movements index, sleep latency, non-REM (Rapid Eye Movement) sleep stage 2 and severity of OSA. Conclusion: The study yielded a simple and feasible screening ML-based model for the early identification of NT1 in patients with OSA, which warrants further verification in more extensive clinical practices.

Ferroptotic therapy in cancer: benefits, side effects, and risks.

Ferroptosis is a type of regulated cell death characterized by iron accumulation and uncontrolled lipid peroxidation, leading to plasma membrane rupture and intracellular content release. Originally investigated as a targeted therapy for cancer cells carrying oncogenic RAS mutations, ferroptosis induction now exhibits potential to complement chemotherapy, immunotherapy, and radiotherapy in various cancer types. However, it can lead to side effects, including immune cell death, bone marrow impairment, liver and kidney damage, cachexia (severe weight loss and muscle wasting), and secondary tumorigenesis. In this review, we discuss the advantages and offer an overview of the diverse range of documented side effects. Furthermore, we examine the underlying mechanisms and explore potential strategies for side effect mitigation.

Development and validation of a machine learning model for prediction of comorbid major depression disorder among narcolepsy type 1.

BACKGROUND: Major depression disorder (MDD) forms a common psychiatric comorbidity among patients with narcolepsy type 1 (NT1), yet its impact on patients with NT1 is often overlooked by neurologists. Currently, there is a lack of effective methods for accurately predicting MDD in patients with NT1. OBJECTIVE: This study utilized machine learning (ML) algorithms to identify critical variables and developed the prediction model for predicting MDD in patients with NT1. METHODS: The study included 267 NT1 patients from four sleep centers. The diagnosis of comorbid MDD was based on Diagnostic and Statistical Manual of Mental Disorders fifth edition (DSM-5). ML models, including six full models and six compact models, were developed using a training set. The performance of these models was compared in the testing set, and the optimal model was evaluated in the testing set. Various evaluation metrics, such as Area under the receiver operating curve (AUC), precision-recall (PR) curve and calibration curve were employed to assess and compare the performance of the ML models. Model interpretability was demonstrated using SHAP. RESULT: In the testing set, the logistic regression (LG) model demonstrated superior performance compared to other ML models based on evaluation metrics such as AUC, PR curve, and calibration curve. The top eight features used in the LG model, ranked by feature importance, included social impact scale (SIS) score, narcolepsy severity scale (NSS) score, total sleep time, body mass index (BMI), education years, age of onset, sleep efficiency, sleep latency. CONCLUSION: The study yielded a straightforward and practical ML model for the early identification of MDD in patients with NT1. A web-based tool for clinical applications was developed, which deserves further verification in diverse clinical settings.

Dorsal root ganglion-derived exosomes deteriorate neuropathic pain by activating microglia via the microRNA-16-5p/HECTD1/HSP90 axis.

BACKGROUND: The activated microglia have been reported as pillar factors in neuropathic pain (NP) pathology, but the molecules driving pain-inducible microglial activation require further exploration. In this study, we investigated the effect of dorsal root ganglion (DRG)-derived exosomes (Exo) on microglial activation and the related mechanism. METHODS: A mouse model of NP was generated by spinal nerve ligation (SNL), and DRG-derived Exo were extracted. The effects of DRG-Exo on NP and microglial activation in SNL mice were evaluated using behavioral tests, HE staining, immunofluorescence, and western blot. Next, the differentially enriched microRNAs (miRNAs) in DRG-Exo-treated microglia were analyzed using microarrays. RT-qPCR, RNA pull-down, dual-luciferase reporter assay, and immunofluorescence were conducted to verify the binding relation between miR-16-5p and HECTD1. Finally, the effects of ubiquitination modification of HSP90 by HECTD1 on NP progression and microglial activation were investigated by Co-IP, western blot, immunofluorescence assays, and rescue experiments. RESULTS: DRG-Exo aggravated NP resulting from SNL in mice, promoted the activation of microglia in DRG, and increased neuroinflammation. miR-16-5p knockdown in DRG-Exo alleviated the stimulating effects of DRG-Exo on NP and microglial activation. DRG-Exo regulated the ubiquitination of HSP90 through the interaction between miR-16-5p and HECTD1. Ubiquitination alteration of HSP90 was involved in microglial activation during NP. CONCLUSIONS: miR-16-5p shuttled by DRG-Exo regulated the ubiquitination of HSP90 by interacting with HECTD1, thereby contributing to the microglial activation in NP.

The role of pre-onset hair hormone in predicting the prognosis of patients with severe pneumonia and acute COVID-19 outbreak.

Numerous research works have investigated the potential impact of endocrine hormones on the severity of COVID-19-related pneumonia in individuals. However, there are few studies on the effect of pre-onset neuroendocrine hormones on the prognosis of COVID-19 patients. This study looked into the prognostic value of pre-onset hair hormone levels in COVID-19 infected individuals. This study included 27 patients with COVID-19 and collected patient information and laboratory indicators. The hormone levels in hair were determined by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Within 28 days, 63 % of the patients in this study passed away. With 28-day mortality as the outcome index, urea nitrogen, CURB-65 score and pneumonia severity score (PSI) of 2 groups were statistically significant (P < 0.05). Among all hormone levels detected in hair, only progesterone level was substantially correlated negatively with COVID-19 patients' 28-day mortality(P < 0.05). The level of progesterone in hair was substantially adversely connected with the death rate at 28 days of COVID-19 patients, according to correlation and logistic regression analysis(P < 0.05). Among patients with COVID-19 pneumonia, hair progesterone levels were strongly associated with 28-day mortality, which emphasizes hair progesterone's importance as a prognostic factor.

Eukaryotic translation initiation factor EIF4G1 p.Ser637Cys mutation in a family with Parkinson's disease with antecedent essential tremor.

Essential tremor (ET) and Parkinson's disease (PD) are common chronic movement disorders that can cause a substantial degree of disability. However, the etiology underlying these two conditions remains poorly understood. In the present study, Whole-exome sequencing of peripheral blood samples from the proband and Sanger sequencing of the other 18 family members, and pedigree analysis of four generations of 29 individuals with both ET and PD in a nonconsanguineous Chinese family were performed. Specifically, family members who had available medical information, including historical documentation and physical examination records, were included. A novel c.1909A>T (p.Ser637Cys) missense mutation was identified in the eukaryotic translation initiation factor 4γ1 (EIF4G1) gene as the candidate likely responsible for both conditions. In total, 9 family members exhibited tremor of the bilateral upper limbs and/or head starting from ages of ≥40 years, 3 of whom began showing evidence of PD in their 70s. Eukaryotic initiation factor 4 (eIF4)G1, a component of the translation initiation complex eIF4F, serves as a scaffold protein that interacts with many initiation factors and then binds to the 40S ribosomal subunit. The EIF4G1 (p.Ser637Cys) might inhibit the recruitment of the mRNA to the ribosome. In conclusion, the results from the present study suggested that EIF4G1 may be responsible for the hereditary PD with 'antecedent ET' reported in the family assessed.

Hypoxia stimulates CTC-platelet cluster formation to promote breast cancer metastasis.

Circulating tumor cell clusters/micro-emboli (CTM) possess greater metastatic capacity and survival advantage compared to individual circulating tumor cell (CTC). However, the formation of CTM subtypes and their role in tumor metastasis remain unclear. In this study, we used a microfluidic Cluster-Chip with easy operation and high efficiency to isolate CTM from peripheral blood, which confirmed their correlation with clinicopathological features and identified the critical role of CTC-platelet clusters in breast cancer metastasis. The correlation between platelets and CTM function was further confirmed in a mouse model and RNA sequencing of CTM identified high-expressed genes related to hypoxia stimulation and platelet activation which possibly suggested the correlation of hypoxia and CTC-platelet cluster formation. In conclusion, we successfully developed the Cluster-Chip platform to realize the clinical capture of CTMs and analyze the biological properties of CTC-platelet clusters, which could benefit the design of potential treatment regimens to prevent CTM-mediated metastasis and tumor malignant progression.

TEAD4 activates PCSK9 to promote stomach adenocarcinoma cell stemness through fatty acid metabolism.

INTRODUCTION: This study attempted to investigate how PCSK9 influences the stemness of stomach adenocarcinoma (STAD) cells. METHODS: CCK-8 and sphere formation assays were used to detect cell viability and stemness. qRT-PCR and western blot were used to detect PCSK9 and TEAD4 expression. The binding relationship was verified by dual luciferase and chromatin immunoprecipitation (ChIP) assays. The effect of TEAD4 activating PCSK9 on the stemness of STAD cells was detected by bioinformatics, BODIPY 493/503, Oil red O, western blot, and kits. In vivo experiments verified the role of the TEAD4/PCSK9 axis in tumor formation in nude mice. RESULTS: PCSK9 and TEAD4 were highly expressed in STAD. PCSK9 was enriched in the FAM pathway. PCSK9 activated the fatty acid metabolism and promoted the proliferation and stemness of STAD cells. TEAD4 as a transcription factor upstream of PCSK9.Cell experiments revealed that knockdown of PCSK9 inhibited STAD cell stemness, whereas further addition of fatty acid inhibitors could attenuate the promoting effect on STAD cell stemness brought by STAD overexpression. Rescue experiments showed overexpressed PCSK9 exerted an inhibitory effect on the stemness of STAD cells brought by TEAD4 knockdown. The hypothesis that TEAD4/PCSK9 axis can promote STAD cell growth was confirmed by in vivo experiments. CONCLUSION: Transcription factor TEAD4 could activate PCSK9 to promote the stemness of STAD cells through FAM. These results added weight to the assumption that TEAD4/PCSK9 axis has the potential to be the therapeutic target that inhibits CSC in STAD.

Case report: Treatment of psoriasiform dermatitis in patients with malignancy.

Psoriasis and atopic dermatitis (AD) are prevalent inflammatory skin disorders, each stemming from diverse factors, and characterized by recurring episodes. In certain complex cases, the clinical and pathological features exhibit overlapping and atypical characteristics, making accurate clinical diagnosis and targeted treatment a challenge. Psoriasiform dermatitis is the term used to describe such cases. Moreover, when patients have a history of malignancy, the situation becomes even more intricate, resulting in limited treatment options. Biologic therapies have transformed the management of immune-mediated inflammatory diseases, including psoriasis and AD. Meanwhile, the safety of biologics in special populations, especially among patients with a history of malignancy, should be underlined. The selective Janus kinase 1 (JAK1) inhibitor abrocitinib has been approved for the treatment of AD and has showed satisfying efficacy and safety in the treatment of psoriasis in clinical trials. Although unreported, JAK1 inhibitors are thought to have the potential to increase the risk of potential tumors. Apremilast, an oral phosphodiesterase (PDE)-4 inhibitor, is approved for moderate to severe plaque psoriasis. It has been investigated for its efficacy in AD, and is not contraindicated in malignancy. This report presents three cases of psoriasiform dermatitis in patients with a history of malignancy, showcasing significant improvement following treatment with systemic glucocorticoid, abrocitinib, or apremilast.

[Diagnosis and treatment of subglottic mass（report of 5 cases）].

Subglottic masses is very rare. The clinical data of five cases of subglottic mass in our hospital from 2017 to 2022 were summarized, and their clinical manifestations, auxiliary examination findings, treatment plan and pathological features were analyzed. Among the 5 patients, 1 case was subglottic pleomorphic adenoma, 1 case was subglottic granuloma, 1 case was subglottic breast cancer metastasis, 1 case was subglottic primary adenoid cystic carcinoma, and 1 case was immunoglobulin G4-related disease. No recurrence was observed in the patients so far. Subglottic mass is easy to be missed. Therefore, when the lesion is suspected in this area, the examination of ear, nose and throat should be carried out systematically to detect the lesion early and improve the prognosis.

Multi-level feature extraction and reconstruction for 3D MRI image super-resolution.

Magnetic resonance imaging (MRI) is an essential radiology technique in clinical diagnosis, but its spatial resolution may not suffice to meet the growing need for precise diagnosis due to hardware limitations and thicker slice thickness. Therefore, it is crucial to explore suitable methods to increase the resolution of MRI images. Recently, deep learning has yielded many impressive results in MRI image super-resolution (SR) reconstruction. However, current SR networks mainly use convolutions to extract relatively single image features, which may not be optimal for further enhancing the quality of image reconstruction. In this work, we propose a multi-level feature extraction and reconstruction (MFER) method to restore the degraded high-resolution details of MRI images. Specifically, to comprehensively extract different types of features, we design the triple-mixed convolution by leveraging the strengths and uniqueness of different filter operations. For the features of each level, we then apply deconvolutions to upsample them separately at the tail of the network, followed by the feature calibration of spatial and channel attention. Besides, we also use a soft cross-scale residual operation to improve the effectiveness of parameter optimization. Experiments on lesion-free and glioma datasets indicate that our method obtains superior quantitative performance and visual effects when compared with state-of-the-art MRI image SR methods.

The Potential Role of Genic-SSRs in Driving Ecological Adaptation Diversity in Caragana Plants.

Caragana, a xerophytic shrub genus widely distributed in northern China, exhibits distinctive geographical substitution patterns and ecological adaptation diversity. This study employed transcriptome sequencing technology to investigate 12 Caragana species, aiming to explore genic-SSR variations in the Caragana transcriptome and identify their role as a driving force for environmental adaptation within the genus. A total of 3666 polymorphic genic-SSRs were identified across different species. The impact of these variations on the expression of related genes was analyzed, revealing a significant linear correlation (p < 0.05) between the length variation of 264 polymorphic genic-SSRs and the expression of associated genes. Additionally, 2424 polymorphic genic-SSRs were located in differentially expressed genes among Caragana species. Through weighted gene co-expression network analysis, the expressions of these genes were correlated with 19 climatic factors and 16 plant functional traits in various habitats. This approach facilitated the identification of biological processes associated with habitat adaptations in the studied Caragana species. Fifty-five core genes related to functional traits and climatic factors were identified, including various transcription factors such as MYB, TCP, ARF, and structural proteins like HSP90, elongation factor TS, and HECT. The roles of these genes in the ecological adaptation diversity of Caragana were discussed. Our study identified specific genomic components and genes in Caragana plants responsive to heterogeneous habitats. The results contribute to advancements in the molecular understanding of their ecological adaptation, lay a foundation for the conservation and development of Caragana germplasm resources, and provide a scientific basis for plant adaptation to global climate change.

The comparison of pure uterine serous carcinoma and mixed tumor with serous component: a single-institution review of 91 cases.

BACKGROUND: Pure uterine serous carcinoma (p-USC) and mixed tumors with serous component (m-USC) are aggressive subtypes of endometrial cancer associated with high mortality rates. This retrospective study aimed to compare clinicopathologic features and outcomes of p-USC and m-USC in a single center. METHODS: This study retrospectively reviewed patients diagnosed with USC at Peking University People's Hospital between 2008 and 2022. T-tests and chi-square tests were used to compare clinicopathological characteristics between p-USC and m-USC. Kaplan-Meier survival curve and Cox regression analysis were used to analyze the impact of clinical and pathological variables on OS and PFS. RESULTS: Among the 91 patients who underwent surgery, 65.9% (n = 60) were p-USC, and 34.1% (n = 31) were m-USC. Patients with p-USC had earlier menopause (P = 0.0217), a lower rate of progesterone receptor(PR) expression (P < 0.001), and were more likely to have positive peritoneal cytology (P = 0.0464). After a median follow-up time of 40 months, 28 (46.7%) p-USC and 9 (29%) m-USC patients had progression disease, 18 (30%) and 8 (25.8%) patients died of their disease. 5-year PFSR were 51.2% and 75.3%, respectively, and 5-year OS rates were 66% and 67.4%. Kaplan-Meier survival analysis showed that p-USC was more likely to relapse than m-USC (P = 0.034), but there was no significant difference in OS. Cox regression analysis showed that lymph node metastasis and surgical approach were risk factors for OS, and myoinvasion depth ≥ 1/2 was an independent risk factor for PFS. CONCLUSIONS: p-USC was more likely to relapse than m-USC, but there was no significant difference in OS between the two subtypes.

Sodium butyrate improves mitochondrial function and kidney tissue injury in diabetic kidney disease via the AMPK/PGC-1α pathway.

PURPOSE: Investigate the mechanism of how sodium butyrate (NaBut) improves mitochondrial function and kidney tissue injury in diabetic kidney disease (DKD) via the AMPK/PGC-1α pathway. METHODS: Assess the effects of NaBut on glucose and insulin tolerance, urine, and gut microbial composition in db/db and db/m mice. Use flow cytometry and western blotting to detect the effects of NaBut on apoptosis, kidney mitochondrial function, and AMPK/PGC-1α signaling. Use HK-2 cells induced by high glucose (HG) to establish the DKD model in vitro and detect changes in the AMPK/PGC-1α signaling pathway and mitochondrial function after NaBut intervention. RESULTS: NaBut attenuated blood glucose levels and reversed increases in urine and serum levels of glucose, BUN, Ucr, TG, TC, and UAE in db/db mice. NaBut improved insulin tolerance, reversed PGC-1α and p-AMPK expression level in the kidneys of db/db mice, and improved lipid accumulation and mitochondrial function. NaBut was able to reverse the effects of elevated glucose, compound C, and siRNA-PGC on ROS and ATP levels. Additionally, it increased protein expression of PGC-1α and p-AMPK. CONCLUSION: NaBut activates the kidney mitochondrial AMPK/PGC-1α signaling pathway and improves mitochondrial dysfunction in DKD, thus protecting kidney tissue in vitro and in vivo.

A biomimetic liver cancer on-a-chip reveals a critical role of LIPOCALIN-2 in promoting hepatocellular carcinoma progression.

Hepatic stellate cells (HSCs) represent a significant component of hepatocellular carcinoma (HCC) microenvironments which play a critical role in tumor progression and drug resistance. Tumor-on-a-chip technology has provided a powerful in vitro platform to investigate the crosstalk between activated HSCs and HCC cells by mimicking physiological architecture with precise spatiotemporal control. Here we developed a tri-cell culture microfluidic chip to evaluate the impact of HSCs on HCC progression. On-chip analysis revealed activated HSCs contributed to endothelial invasion, HCC drug resistance and natural killer (NK) cell exhaustion. Cytokine array and RNA sequencing analysis were combined to indicate the iron-binding protein LIPOCALIN-2 (LCN-2) as a key factor in remodeling tumor microenvironments in the HCC-on-a-chip. LCN-2 targeted therapy demonstrated robust anti-tumor effects both in vitro 3D biomimetic chip and in vivo mouse model, including angiogenesis inhibition, sorafenib sensitivity promotion and NK-cell cytotoxicity enhancement. Taken together, the microfluidic platform exhibited obvious advantages in mimicking functional characteristics of tumor microenvironments and developing targeted therapies.

First-principles study of two-dimensional half-metallic ferromagnetism in CrSiSe4monolayer.

Two-dimensional (2D) ferromagnetic (FM) half-metallic materials have attracted intensive attention due to their unique electronic and magnetic properties and potential applications in spintronic devices. In this study, we predicted a stable 2D half-metallic material monolayer CrSiSe4using first-principles density functional theory. The structure, electronic and magnetic properties were systematically studied. The calculations show that the monolayer CrSiSe4is a dynamically stable FM half-metallic material. The spin-dependent transport properties and the Curie temperature up to 239 K are demonstrated. The spin band gap of monolayer CrSiSe4was about 0.83 eV by the the Heyd-Scuseria-Ernzerhof function calculation. The magnetic anisotropy energy of each Cr atom in the monolayer of CrSiSe4is-552.3µeV. When the applied biaxial tensile strain is greater than 2%, monolayer CrSiSe4spin-up conduction band and valence band will show a band gap at the Fermi level, and the electronic properties change from a half-metal to a semiconductor. Thus, the monolayer CrSiSe4can provide an ideal candidate material for exploring 2D magnetic and spintronics experiments.

Dual-responsive probe and DNA interstrand crosslink precursor target the unique redox status of cancer cells.

Elevated GSH and H2O2 in cancer cells is sometimes doubted due to their contrary reactivities. Here, we construct a dual-responsive fluorescent probe to confirm the conclusion, and employ this to exploit a redox-inducible DNA interstrand crosslink (ICL) precursor. It crosslinks DNA upon activation by GSH and H2O2, affording an alternative dual-responsive strategy.

A decoupled Bayesian method for snake robot control in unstructured environment.

This paper presents a method which avoids the common practice of using a complex coupled snake robot model and performing kinematic analysis for control in cluttered environments. Instead, we introduce a completely decoupled dynamical Bayesian formulation with respect to interacted snake robot links and environmental objects, which requires much lower complexity for efficient and robust control. When a snake robot does not interact with obstacles, it runs by a simple serpenoid controller. However, when it exhibits interaction with environments, defined as close proximity or collision with targets and/or obstacles, we extend the conventional Bayesian framework by modeling such interactions in terms of stimuli. The proposed 'multi-neural-stimulus function' represents the cumulative effect of both external environmental influences and internal constraints of the snake robot. It implicitly handles the 'unexpected collision' problem and thus solve the difficult data association and shape adjustment problems for snake robot control in an innovative way. Preliminary experimental results have demonstrated promising performance of the proposed method comparing with the state-of-the-art.

Compound heterozygous mutations in tripeptidyl peptidase 1 cause rare autosomal recessive spinocerebellar ataxia type 7: A case report.

BACKGROUND: Spinocerebellar ataxia recessive type 7 (SCAR7) is a rare clinical manifestation beginning in childhood or adolescence. SCAR7 is caused by tripeptidyl peptidase 1 (TPP1) gene mutations, and presents with cerebellar ataxia, pyramidal signs, neurocognitive impairment, deep paresthesia, and cerebellar atrophy. CASE SUMMARY: Here, we describe a 25-year-old female patient in China who presented with increasing difficulty walking, falling easily, shaking limbs, instability holding items, slurred speech, coughing when drinking, palpitations, and frequent hunger and overeating. Magnetic resonance imaging showed cerebellar atrophy. Whole exome sequencing detected two compound heterozygous mutations in the TPP1 gene: c.1468G>A p.Glu490Lys and c.1417G>A p.Gly473Arg. Considering the patient's clinical presentation and genetic test results, we hypothesized that complex heterozygous mutations cause TPP1 enzyme deficiency, which may lead to SCAR7. CONCLUSION: We report the first case of SCAR7 from China. We also identify novel compound heterozygous mutations in the TPP1 gene associated with SCAR7, expanding the range of known disease-causing mutations for SCAR7.