Epileptic brain network mechanisms and neuroimaging techniques for the brain network.

Epilepsy can be defined as a dysfunction of the brain network, and each type of epilepsy involves different brain-network changes that are implicated differently in the control and propagation of interictal or ictal discharges. Gaining more detailed information on brain network alterations can help us to further understand the mechanisms of epilepsy and pave the way for brain network-based precise therapeutic approaches in clinical practice. An increasing number of advanced neuroimaging techniques and electrophysiological techniques such as diffusion tensor imaging-based fiber tractography, diffusion kurtosis imaging-based fiber tractography, fiber ball imaging-based tractography, electroencephalography, functional magnetic resonance imaging, magnetoencephalography, positron emission tomography, molecular imaging, and functional ultrasound imaging have been extensively used to delineate epileptic networks. In this review, we summarize the relevant neuroimaging and neuroelectrophysiological techniques for assessing structural and functional brain networks in patients with epilepsy, and extensively analyze the imaging mechanisms, advantages, limitations, and clinical application ranges of each technique. A greater focus on emerging advanced technologies, new data analysis software, a combination of multiple techniques, and the construction of personalized virtual epilepsy models can provide a theoretical basis to better understand the brain network mechanisms of epilepsy and make surgical decisions.

Establishment of a prognosis predictive model for liver cancer based on expression of genes involved in the ubiquitin-proteasome pathway.

BACKGROUND: The ubiquitin-proteasome pathway (UPP) has been proven to play important roles in cancer. AIM: To investigate the prognostic significance of genes involved in the UPP and develop a predictive model for liver cancer based on the expression of these genes. METHODS: In this study, UPP-related E1, E2, E3, deubiquitylating enzyme, and proteasome gene sets were obtained from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, aiming to screen the prognostic genes using univariate and multivariate regression analysis and develop a prognosis predictive model based on the Cancer Genome Atlas liver cancer cases. RESULTS: Five genes (including autophagy related 10, proteasome 20S subunit alpha 8, proteasome 20S subunit beta 2, ubiquitin specific peptidase 17 like family member 2, and ubiquitin specific peptidase 8) were proven significantly correlated with prognosis and used to develop a prognosis predictive model for liver cancer. Among training, validation, and Gene Expression Omnibus sets, the overall survival differed significantly between the high-risk and low-risk groups. The expression of the five genes was significantly associated with immunocyte infiltration, tumor stage, and postoperative recurrence. A total of 111 differentially expressed genes (DEGs) were identified between the high-risk and low-risk groups and they were enriched in 20 and 5 gene ontology and KEGG pathways. Cell division cycle 20, Kelch repeat and BTB domain containing 11, and DDB1 and CUL4 associated factor 4 like 2 were the DEGs in the E3 gene set that correlated with survival. CONCLUSION: We have constructed a prognosis predictive model in patients with liver cancer, which contains five genes that associate with immunocyte infiltration, tumor stage, and postoperative recurrence.

Multilocular thymic cysts can be easily misdiagnosed as malignant tumor on computer tomography: A case report.

BACKGROUND: Multilocular thymic cyst (MTC) is a rare mediastinal lesion which is considered to occur in the process of acquired inflammation. It is usually characterized by well-defined cystic density and is filled with transparent liquid. CASE SUMMARY: We report on a 39-year-old male with a cystic-solid mass in the anterior mediastinum. Computer tomography (CT) imaging showed that the mass was irregular with unclear boundaries. After injection of contrast agent, there was a slight enhancement of stripes and nodules. According to CT findings, it was diagnosed as thymic cancer. CONCLUSION: After surgery, MTC accompanied by bleeding and infection was confirmed by pathological examination. The main lesson of this case was that malignant thymic tumor and MTC of the anterior mediastinum sometimes exhibit similar CT findings. Caution is necessary in clinical work to avoid misdiagnosis.

Acute ischemic stroke in tuberculous meningitis.

Background: The underlying mechanism for stroke in patients with tuberculous meningitis (TBM) remains unclear. This study aimed to investigate the predictors of acute ischemic stroke (AIS) in TBM and whether AIS mediates the relationship between inflammation markers and functional disability. Methods: TBM patients admitted to five hospitals between January 2011 and December 2021 were consecutively observed. Generalized linear mixed model and subgroup analyses were performed to investigate predictors of AIS in patients with and without vascular risk factors (VAFs). Mediation analyses were performed to explore the potential causal chain in which AIS may mediate the relationship between neuroimaging markers of inflammation and 90-day functional outcomes. Results: A total of 1,353 patients with TBM were included. The percentage rate of AIS within 30 days after admission was 20.4 (95% CI, 18.2-22.6). A multivariate analysis suggested that age ≥35 years (OR = 1.49; 95% CI, 1.06-2.09; P = 0.019), hypertension (OR = 3.56; 95% CI, 2.42-5.24; P < 0.001), diabetes (OR = 1.78; 95% CI, 1.11-2.86; P = 0.016), smoking (OR = 2.88; 95% CI, 1.68-4.95; P < 0.001), definite TBM (OR = 0.19; 95% CI, 0.06-0.42; P < 0.001), disease severity (OR = 2.11; 95% CI, 1.50-2.90; P = 0.056), meningeal enhancement (OR = 1.66; 95% CI, 1.19-2.31; P = 0.002), and hydrocephalus (OR = 2.98; 95% CI, 1.98-4.49; P < 0.001) were associated with AIS. Subgroup analyses indicated that disease severity (P for interaction = 0.003), tuberculoma (P for interaction = 0.008), and meningeal enhancement (P for interaction < 0.001) were significantly different in patients with and without VAFs. Mediation analyses revealed that the proportion of the association between neuroimaging markers of inflammation and functional disability mediated by AIS was 16.98% (95% CI, 7.82-35.12) for meningeal enhancement and 3.39% (95% CI, 1.22-6.91) for hydrocephalus. Conclusion: Neuroimaging markers of inflammation were predictors of AIS in TBM patients. AIS mediates < 20% of the association between inflammation and the functional outcome at 90 days. More attention should be paid to clinical therapies targeting inflammation and hydrocephalus to directly improve functional outcomes.

Lung adenocarcinoma discovered during the follow-up of lung-dominant connective tissue disease: a case report and literature review.

Interstitial lung disease (ILD) can lead to lung cancer, which brings great challenges to differential diagnosis and comprehensive treatment. However, the clinical features of lung-dominant connective tissue disease (LD-CTD) related ILD combined with lung cancer has not been validated. We report the case of an 80-year-old woman with LD-CTD treated regularly with nintedanib who presented progressive dyspnoea and hypoxemia after recurrent viral infections. Her chest computed tomography (CT) showed aggravated interstitial fibrosis in both lower lungs with moderate right pleural effusion. Clinicians should be alert to lung cancer in patients who are experiencing poor responsiveness to treatment or acute progression of ILD. The available literatures about the differential diagnosis of clinical manifestations, imaging, treatment and prognosis of LD-CTD are reviewed and discussed in this study.

Open access EEG dataset of repeated measurements from a single subject for microstate analysis.

Electroencephalography (EEG) microstate analysis is a neuroimaging analytical method that has received considerable attention in recent years and is widely used for analysing EEG signals. EEG is easily influenced by internal and external factors, which can affect the repeatability and stability of EEG microstate analysis. However, there have been few reports and publicly available datasets on the repeatability of EEG microstate analysis. In the current study, a 39-year-old healthy male underwent a total of 60 simultaneous electroencephalography and electrocardiogram measurements over a period of three months. After the EEG recording was completed, magnetic resonance imaging (MRI) was also conducted. To date, this EEG dataset has the highest number of repeated measurements for one individual. The dataset can be used to assess the stability and repeatability of EEG microstates and other analytical methods, to decode resting EEG states among subjects with open eyes, and to explore the stability and repeatability of cortical spatiotemporal dynamics through source analysis with individual MRI.

Treatment for Stanford type B aortic dissection with insufficient anchoring region using castor integrated branched aortic stent graft.

Background: To investigate the clinical efficacy of Castor integrated branched aortic stent graft for the treatment of Stanford type B aortic dissection with insufficient anchoring area. Methods: Retrospective analysis of clinical data of 26 patients with Stanford type B aortic dissection with insufficient anchoring region (<15 mm) treated by Castor branched aortic stent graft from September 2018 to June 2022 at Ganzhou People's Hospital, including 23 acute cases and 3 chronic cases. Results: Surgical procedures were successfully performed in all 26 patients, and during the perioperative period no complications occurred, such as cerebrovascular accident, stenosis or occlusion of left subclavian artery, progression of reverse avulsion of aortic dissection, and paraplegia. During the operation 2 patients had a small amount of type I endoleak, which disappeared during the postoperative follow-up. The other patients had good postoperative follow-up results. Review of the aortic CTA indicated good stent morphology with patency of the left subclavian artery. Conclusions: The Castor integrated branched aortic stent graft expanded the indications for endoluminal treatment for Stanford type B aortic dissection, which can avoid open surgery and has good clinical outcomes.

Response of cotton growth, yield, and water and nitrogen use efficiency to nitrogen application rate and ionized brackish water irrigation under film-mulched drip fertigation.

Introduction: The presence of brackish water resources is significant in addressing the scarcity of freshwater resources, particularly in the Xinjiang region. Studies focused on reducing adverse effect of brackish water irrigation based on using ionized brackish water, as well as on investigating its effects on fibre and oil plant production processes, remain incipient in the literature. Some benefits of this technique are the optimization of the quality and quantity of irrigation water, economy of water absorbed by the plants, improvement in the vegetative growth and productivity compared to irrigation using conventional brackish water. Thus, the aim of the current study is to assess the effect of different nitrogen application rates on soil water and salinity, cotton growth and water and nitrogen use efficiency. Methods: The experimental design consisted of completely randomized design with two water types (ionized and non-ionized) and six nitrogen application rates with four replications. Results: Irrigation conducted with ionized brackish water and different nitrogen application rates had significant effect on the plant height, leaf area index, shoot dry matter, boll number per plant and chlorophyll content. The study also demonstrated significant effects of ionized brackish water on soil water content and soil salinity accumulation. The highest cotton production was achieved with the use of 350 kg·ha-1 of ionized brackish water for irrigation, resulting in an average increase of 11.5% compared to the use of non-ionized brackish water. The nitrogen application exhibits a quadratic relationship with nitrogen agronomic use efficiency and apparent nitrogen use efficiency, while it shows a liner relationship with nitrogen physiological use efficiency and nitrogen partial productivity. After taking into account soil salinity, cotton yield, water and nitrogen use efficiency, the optimal nitrogen application rate for ionized brackish water was determined to be 300 kg·ha-1. Discussion: It is hoped that this study can contribute to improving water management, reducing the environmental impact without implying great costs for the producer.

The Burden of Cancer and Pre-cancerous Conditions Among Transgender Individuals in a Large Healthcare Network.

The current study aimed to examine the prevalence of and risk factors for cancer and pre-cancerous conditions, comparing transgender and cisgender individuals, using 2012-2023 electronic health record data from a large healthcare system. We identified 2,745 transgender individuals using a previously validated computable phenotype and 54,900 matched cisgender individuals. We calculated the prevalence of cancer and pre-cancer related to human papillomavirus (HPV), human immunodeficiency virus (HIV), tobacco, alcohol, lung, breast, colorectum, and built multivariable logistic models to examine the association between gender identity and the presence of cancer or pre-cancer. Results indicated similar odds of developing cancer across gender identities, but transgender individuals exhibited significantly higher risks for pre-cancerous conditions, including alcohol-related, breast, and colorectal pre-cancers compared to cisgender women, and HPV-related, tobacco-related, alcohol-related, and colorectal pre-cancers compared to cisgender men. These findings underscore the need for tailored interventions and policies addressing cancer health disparities affecting the transgender population.

Fabrication of High-Performance Densified Wood via High-Pressure Steam Treatment and Hot-Pressing.

The fabrication of sustainable structural materials with high physical properties to replace engineering plastics is a major challenge for modern industry, and wood, as the most abundant sustainable natural raw material on the planet, has received a great deal of attention from researchers. Researchers have made efforts to enhance the physical properties of wood in order to replace plastics. However, it is also difficult to meet practical demands at a low cost. Herein, we report a simple and efficient top-down strategy to transform bulk natural basswood into a high-performance structural material. This three-step strategy involves partial removal of hemicellulose and lignin via treating basswood by boiling an aqueous mixture of NaOH and Na2SO3, and a high-pressure steam treatment (HPST) was applied to delignified wood followed by hot-pressing, which allowed the wood to absorb moisture uniformly and quickly. HPST-treated dense delignified wood (HDDW) has a tensile strength of ~420 MPa, which is 6.5 times better than natural basswood (~65 MPa). We systematically investigated the various factors affecting the tensile strength of this wood material and explored the reasons why these factors affect the tensile strength, as well as the intrinsic connection between the moisture absorbed through HPST and the increased tensile strength of HDDW. Through our experiments, we realized the enhancement mechanism of HDDW and the optimal experimental conditions for the fabrication of HDDW.

Association between exposure to a mixture of organochlorine pesticides and hyperuricemia in U.S. adults: A comparison of four statistical models.

The association between the exposure of organochlorine pesticides (OCPs) and serum uric acid (UA) levels remained uncertain. In this study, to investigate the combined effects of OCP mixtures on hyperuricemia, we analyzed serum OCPs and UA levels in adults from the National Health and Nutrition Examination Survey (2005-2016). Four statistical models including weighted logistic regression, weighted quantile sum (WQS), quantile g-computation (QGC), and bayesian kernel machine regression (BKMR) were used to assess the relationship between mixed chemical exposures and hyperuricemia. Subgroup analyses were conducted to explore potential modifiers. Among 6,529 participants, the prevalence of hyperuricemia was 21.15%. Logistic regression revealed a significant association between both hexachlorobenzene (HCB) and trans-nonachlor and hyperuricemia in the fifth quintile (OR: 1.54, 95% CI: 1.08-2.19; OR: 1.58, 95% CI: 1.05-2.39, respectively), utilizing the first quintile as a reference. WQS and QGC analyses showed significant overall effects of OCPs on hyperuricemia, with an OR of 1.25 (95% CI: 1.09-1.44) and 1.20 (95% CI: 1.06-1.37), respectively. BKMR indicated a positive trend between mixed OCPs and hyperuricemia, with HCB having the largest weight in all three mixture analyses. Subgroup analyses revealed that females, individuals aged 50 years and above, and those with a low income were more vulnerable to mixed OCP exposure. These results highlight the urgent need to protect vulnerable populations from OCPs and to properly evaluate the health effects of multiple exposures on hyperuricemia using mutual validation approaches.

Dementia is associated with worse procedural outcomes after mitral valve transcatheter edge-to-edge repair.

BACKGROUND: Patients with dementia are at increased risk for adverse events following valvular surgery. Outcomes after mitral transcatheter edge-to-edge repair (TEER) for mitral regurgitation in this vulnerable population are not well understood. METHODS: We queried the National Inpatient Sample database for all hospitalizations for mitral TEER between 2016 and 2019. Patients with a validated diagnosis code for dementia were identified by ICD-10 codes and compared to a matched cohort of non-dementia patients using multivariable regression analysis. The primary outcome was in-hospital mortality. Secondary outcomes were hospital length of stay, discharge to nursing facility, total hospital charges, and in-hospital adverse events. RESULTS: 24,550 hospitalizations for mitral TEER were identified, including 880 patients (3.6 %) with dementia. Dementia was associated with higher in-hospital mortality (OR 4.31, 95 % CI 2.65 to 6.99, p < 0.001), prolonged length of hospital stay (OR 1.33, 95 % CI 1.12 to 1.57, p 0.001), higher discharge rate to nursing facility (OR 2.71, 95 % CI 2.13-3.44, p < 0.001), and higher rate of in-hospital adverse events including delirium (OR 5.88, 95 % CI 4.06 to 8.52, p < 0.001) and acute stroke (OR 8.87, 95 % CI 5.01 to 15.70, p < 0.001). CONCLUSIONS: Dementia is associated with worse post-procedural outcomes after mitral TEER. Further investigation is needed to elucidate mechanisms of poor clinical outcomes and guide shared decision-making in this vulnerable population.

Identifying social determinants of health from clinical narratives: A study of performance, documentation ratio, and potential bias.

OBJECTIVE: To develop a natural language processing (NLP) package to extract social determinants of health (SDoH) from clinical narratives, examine the bias among race and gender groups, test the generalizability of extracting SDoH for different disease groups, and examine population-level extraction ratio. METHODS: We developed SDoH corpora using clinical notes identified at the University of Florida (UF) Health. We systematically compared 7 transformer-based large language models (LLMs) and developed an open-source package - SODA (i.e., SOcial DeterminAnts) to facilitate SDoH extraction from clinical narratives. We examined the performance and potential bias of SODA for different race and gender groups, tested the generalizability of SODA using two disease domains including cancer and opioid use, and explored strategies for improvement. We applied SODA to extract 19 categories of SDoH from the breast (n = 7,971), lung (n = 11,804), and colorectal cancer (n = 6,240) cohorts to assess patient-level extraction ratio and examine the differences among race and gender groups. RESULTS: We developed an SDoH corpus using 629 clinical notes of cancer patients with annotations of 13,193 SDoH concepts/attributes from 19 categories of SDoH, and another cross-disease validation corpus using 200 notes from opioid use patients with 4,342 SDoH concepts/attributes. We compared 7 transformer models and the GatorTron model achieved the best mean average strict/lenient F1 scores of 0.9122 and 0.9367 for SDoH concept extraction and 0.9584 and 0.9593 for linking attributes to SDoH concepts. There is a small performance gap (∼4%) between Males and Females, but a large performance gap (>16 %) among race groups. The performance dropped when we applied the cancer SDoH model to the opioid cohort; fine-tuning using a smaller opioid SDoH corpus improved the performance. The extraction ratio varied in the three cancer cohorts, in which 10 SDoH could be extracted from over 70 % of cancer patients, but 9 SDoH could be extracted from less than 70 % of cancer patients. Individuals from the White and Black groups have a higher extraction ratio than other minority race groups. CONCLUSIONS: Our SODA package achieved good performance in extracting 19 categories of SDoH from clinical narratives. The SODA package with pre-trained transformer models is available at https://github.com/uf-hobi-informatics-lab/SODA_Docker.

The greatest loss of unpleasant smells may be related to the risk of more severe PD symptoms.

Background: Limited research has explored the relationship between the valence of olfactory dysfunction and PD clinical symptoms. This study aimed to investigate correlations between the emotional valence of olfactory impairment and different domains of PD symptoms. Methods: PD patients who fulfilled the clinically probable PD diagnostic criteria of the International Parkinson and Movement Disorder Society Clinical Diagnostic Criteria for Parkinson's Disease were recruited from the Center for Parkinson and Movement Disorders at Taichung Veterans General Hospital between October 2016 and April 2022. Demographic data and serial clinical assessments were collected, including the traditional Chinese version of the University of Pennsylvania Smell Identification Test (UPSIT-TC) and Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS). Thirty-five odors from the UPSIT-TC were classified into neutral, pleasant or unpleasant groups. Group comparisons, correlation analyses, and linear regression analyses were conducted to examine the relationship between olfactory impairment of UPSIT-TC odors, considering emotional valence, and MDS-UPDRS subscores across various domains. Results: A total of 176 PD patients were recruited for analysis. Patients in the predominantly neutral/unpleasant odor impairment groups had higher MDS-UPDRS part III scores compared to those in the predominantly pleasant odor impairment group (pleasant vs. neutral vs. unpleasant odor impairment groups: 26.79 ± 13.59 vs. 35.33 ± 16.36 vs. 31.57 ± 12.37, p = 0.009). This trend was also noted in MDS-UPDRS rigidity, bradykinesia, and akinetic-rigid subscores (p = 0.003, p = 0.012, and p = 0.001, respectively). Correlation analysis revealed a weak but significant correlation between rigidity/akinetic-rigid subscores and misidentification numbers for neutral/unpleasant odors (all p < 0.05), with age, gender, LEDD, and disease duration as covariates. All significances were retained in the linear regression analysis. Conclusion: Our results emphasize the link between olfactory impairment of specific emotional valence, neutral/unpleasant odors, and PD severity, particularly with respect to akinetic-rigid symptoms. A concise olfactory test that focuses on both neutral and unpleasant odors may offer deeper insights into PD symptoms.

Deep causal learning for pancreatic cancer segmentation in CT sequences.

Segmenting the irregular pancreas and inconspicuous tumor simultaneously is an essential but challenging step in diagnosing pancreatic cancer. Current deep-learning (DL) methods usually segment the pancreas or tumor independently using mixed image features, which are disrupted by surrounding complex and low-contrast background tissues. Here, we proposed a deep causal learning framework named CausegNet for pancreas and tumor co-segmentation in 3D CT sequences. Specifically, a causality-aware module and a counterfactual loss are employed to enhance the DL network's comprehension of the anatomical causal relationship between the foreground elements (pancreas and tumor) and the background. By integrating causality into CausegNet, the network focuses solely on extracting intrinsic foreground causal features while effectively learning the potential causality between the pancreas and the tumor. Then based on the extracted causal features, CausegNet applies a counterfactual inference to significantly reduce the background interference and sequentially search for pancreas and tumor from the foreground. Consequently, our approach can handle deformable pancreas and obscure tumors, resulting in superior co-segmentation performance in both public and real clinical datasets, achieving the highest pancreas/tumor Dice coefficients of 86.67%/84.28%. The visualized features and anti-noise experiments further demonstrate the causal interpretability and stability of our method. Furthermore, our approach improves the accuracy and sensitivity of downstream pancreatic cancer risk assessment task by 12.50% and 50.00%, respectively, compared to experienced clinicians, indicating promising clinical applications.

Acupuncture alleviates inflammatory pain by activating CXCL1/CXCR2 signaling in the primary somatosensory cortex in adjuvant induced arthritis rats. / S1脑区CXCL1/CXCR2å‚ä¸Žé’ˆåˆºæ”¹å–„ä½å‰‚æ€§å ³èŠ‚ç‚Žå¤§é¼ ç‚Žæ€§ç—›çš„ä½œç”¨æœºåˆ¶.

OBJECTIVES: To observe whether acupuncture up-regulates chemokine CXC ligand 1 (CXCL1) in the brain to play an analgesic role through CXCL1/chemokine CXC receptor 2 (CXCR2) signaling in adjuvant induced arthritis (AIA) rats, so as to reveal its neuro-immunological mechanism underlying improvement of AIA. METHODS: BALB/c mice with relatively stable thermal pain reaction were subjected to planta injection of complete Freund adjuvant (CFA) for establishing AIA model, followed by dividing the AIA mice into simple AF750 (fluorochrome) and AF750+CXCL1 groups (n=2 in each group). AF750 labeled CXCL1 recombinant protein was then injected into the mouse's tail vein to induce elevation of CXCL1 level in blood for simulating the effect of acupuncture stimulation which has been demonstrated by our past study. In vivo small animal imaging technology was used to observe the AF750 and AF750+CXCL1-labelled target regions. After thermal pain screening, the Wistar rats with stable pain reaction were subjected to AIA modeling by injecting CFA into the rat's right planta, then were randomized into model and manual acupuncture groups (n=12 in each group). Other 12 rats that received planta injection of saline were used as the control group. Manual acupuncture (uniform reinforcing and reducing manipulations) was applied to bilateral "Zusanli" (ST36) for 4×2 min, with an interval of 5 min between every 2 min, once daily for 7 days. The thermal pain threshold was assessed by detecting the paw withdrawal latency (PWL) using a thermal pain detector. The contents of CXCL1 in the primary somatosensory cortex (S1), medial prefrontal cortex, nucleus accumbens, amygdala, periaqueductal gray and rostroventromedial medulla regions were assayed by using ELISA, and the expression levels of CXCL1, CXCR2 and mu-opioid receptor (MOR) mRNA in the S1 region were detected using real time-quantitative polymerase chain reaction. The immune-fluorescence positive cellular rate of CXCL1 and CXCR2 in S1 region was observed after immunofluorescence stain. The immunofluorescence double-stain of CXCR2 and astrocyte marker glial fibrillary acidic protein (GFAP) or neuron marker NeuN or MOR was used to determine whether there is a co-expression between them. RESULTS: In AIA mice, results of in vivo experiments showed no obvious enrichment signal of AF750 or AF750+CXCL1 in any organ of the body, while in vitro experiments showed that there was a stronger fluorescence signal of CXCL1 recombinant protein in the brain. In rats, compared with the control group, the PWL from day 0 to day 7 was significantly decreased (P<0.01) and the expression of CXCR2 mRNA in the S1 region significantly increased in the model group (P<0.05), while in comparison with the model group, the PWL from day 2 to day 7, CXCL1 content, CXCR2 mRNA expression and CXCR2 content, and MOR mRNA expression in the S1 region were significantly increased in the manual acupuncture group (P<0.05, P<0.01). Immunofluorescence stain showed that CXCR2 co-stained with NeuN and MOR in the S1 region, indicating that CXCR2 exists in neurons and MOR-positive neurons but not in GFAP positive astrocytes. CONCLUSIONS: Acupuncture can increase the content of CXCL1 in S1 region, up-regulate CXCR2 on neurons in the S1 region and improve MOR expression in S1 region of AIA rats, which may contribute to its effect in alleviating inflammatory pain.

In Situ Polymerization Facilitating Practical High-Safety Quasi-Solid-State Batteries.

Quasi-solid-state batteries (QSSBs) are gaining widespread attention as a promising solution to improve battery safety performance. However, the safety improvement and the underlying mechanisms of QSSBs remain elusive. Herein, a novel strategy combining high-safety ethylene carbonate-free liquid electrolyte and in situ polymerization technique is proposed to prepare practical QSSBs. The Ah-level QSSBs with LiNi0.83Co0.11Mn0.06O2 cathode and graphite-silicon anode demonstrate significantly improved safety features without sacrificing electrochemical performance. As evidenced by accelerating rate calorimetry tests, the QSSBs exhibit increased self-heating temperature and onset temperature (T2), and decreased temperature rise rate during thermal runaway (TR). The T2 has a maximum increase of 48.4 °C compared to the conventional liquid batteries. Moreover, the QSSBs do not undergo TR until 180 °C (even 200 °C) during the hot-box tests, presenting significant improvement compared to the liquid batteries that run into TR at 130 °C. Systematic investigations show that the in situ formed polymer skeleton effectively mitigates the exothermic reactions between lithium salts and lithiated anode, retards the oxygen release from cathode, and inhibits crosstalk reactions between cathode and anode at elevated temperatures. The findings offer an innovative solution for practical high-safety QSSBs and open up a new sight for building safer high-energy-density batteries.

Toll-like receptor signaling pathway involved in pathogenesis of thromboangiitis obliterans through activating of NF-κB.

OBJECTIVES: The pathogenic mechanisms of Thromboangiitis Obliterans (TAO) are not entirely known and autoimmune inflammation plays a vital role in the initiation and continuance of TAO activity. The authors investigated in this study the role of the TLR signaling pathway in the pathogenesis of TAO. METHODS: First, the authors detected the expressions of MyD88, TRIF and NF-κB in vascular walls of 46 patients with TAO and 32 patients with trauma and osteosarcoma by western blot assay. Second, the authors detected the cellular localization of MyD88, TRIF and NF-κB in vascular walls of patients with TAO by immunofluorescent assay. RESULTS: The protein expressions of MyD88, TRIF and NF-κB were much higher in vascular walls of TAO patients (p < 0.05). Higher expressions of MyD88 and NF-κB were detected both on vascular endothelial and vascular smooth muscle cells of TAO patients. However, higher expression of TRIF was just detected on vascular smooth muscle cells of TAO patients. CONCLUSIONS: These dates suggest that the TLR signaling pathway might play an important role in the pathogenesis of TAO, it might induce vasospasm, vasculitis and thrombogenesis to lead to the pathogenesis and progression of TAO.

Effect of Eligibility Criteria on Patients' Survival and Serious Adverse Events in Colorectal Cancer Drug Trials.

This study investigates the impact of clinical trial eligibility criteria on patient survival and serious adverse events (SAEs) in colorectal cancer (CRC) drug trials using real-world data. We utilized the OneFlorida+ network's data repository, conducting a retrospective analysis of CRC patients receiving FDA-approved first-line metastatic treatments. Propensity score matching created balanced case-control groups, which were evaluated using survival analysis and machine learning algorithms to assess the effects of eligibility criteria. Our study included 68,375 patients, with matched case-control groups comprising 1,126 patients each. Survival analysis revealed ethnicity and race, along with specific medical history (eligibility criteria), as significant survival outcome predictors. Machine learning models, particularly the XgBoost regressor, were employed to analyze SAEs, indicating that age and study groups were notable factors in SAEs occurrence. The study's findings highlight the importance of considering patient demographics and medical history in CRC trial designs.

Machine Learning Prediction of Autism Spectrum Disorder Through Linking Mothers' and Children's Electronic Health Record Data.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder typically diagnosed in children. Early detection of ASD, particularly in girls who are often diagnosed late, can aid long-term development for children. We aimed to develop machine learning models for predicting ASD diagnosis in children, both boys and girls, using child-mother linked electronic health records (EHRs) data from a large clinical research network. Model features were children and mothers' risk factors in EHRs, including maternal health factors. We tested XGBoost and logistic regression with Random Oversampling (ROS) and Random Undersampling (RUS) to address imbalanced data. Logistic regression with RUS considering a three-year observation window for children's risk factors achieved the best performance for predicting ASD among the overall study population (AUROC = 0.798), boys (AUROC = 0.786), and girls (AUROC = 0.791). We calculated SHAP values to quantify the impacts of important clinical and sociodemographic risk factors.