Antiferromagnetic phase transition in a 3D fermionic Hubbard model.

The fermionic Hubbard model (FHM)1 describes a wide range of physical phenomena resulting from strong electron-electron correlations, including conjectured mechanisms for unconventional superconductivity. Resolving its low-temperature physics is, however, challenging theoretically or numerically. Ultracold fermions in optical lattices2,3 provide a clean and well-controlled platform offering a path to simulate the FHM. Doping the antiferromagnetic ground state of a FHM simulator at half-filling is expected to yield various exotic phases, including stripe order4, pseudogap5, and d-wave superfluid6, offering valuable insights into high-temperature superconductivity7-9. Although the observation of antiferromagnetic correlations over short10 and extended distances11 has been obtained, the antiferromagnetic phase has yet to be realized as it requires sufficiently low temperatures in a large and uniform quantum simulator. Here we report the observation of the antiferromagnetic phase transition in a three-dimensional fermionic Hubbard system comprising lithium-6 atoms in a uniform optical lattice with approximately 800,000 sites. When the interaction strength, temperature and doping concentration are finely tuned to approach their respective critical values, a sharp increase in the spin structure factor is observed. These observations can be well described by a power-law divergence, with a critical exponent of 1.396 from the Heisenberg universality class12. At half-filling and with optimal interaction strength, the measured spin structure factor reaches 123(8), signifying the establishment of an antiferromagnetic phase. Our results provide opportunities for exploring the low-temperature phase diagram of the FHM.

FNPC-SAM: Uncertainty-Guided False Negative/Positive Control for SAM on Noisy Medical Images.

The Segment Anything Model (SAM) is a recently developed all-range foundation model for image segmentation. It can use sparse manual prompts such as bounding boxes to generate pixel-level segmentation in natural images but struggles in medical images such as low-contrast, noisy ultrasound images. We propose a refined test-phase prompt augmentation technique designed to improve SAM's performance in medical image segmentation. The method couples multi-box prompt augmentation and an aleatoric uncertainty-based false-negative (FN) and false-positive (FP) correction (FNPC) strategy. We evaluate the method on two ultrasound datasets and show improvement in SAM's performance and robustness to inaccurate prompts, without the necessity for further training or tuning. Moreover, we present the Single-Slice-to-Volume (SS2V) method, enabling 3D pixel-level segmentation using only the bounding box annotation from a single 2D slice. Our results allow efficient use of SAM in even noisy, low-contrast medical images. The source code has been released at: https://github.com/MedICL-VU/FNPC-SAM.

Improvement effects of a novel Chinese herbal formula in imiquimod and IL-23-stimulated mouse models of psoriasis.

BACKGROUND: Psoriasis is a long-term inflammatory skin disease. A novel herbal formula containing nine Chinese herbal medicines, named Inflammation Skin Disease Formula (ISDF), has been prescribed in clinics for decades. AIMS: To investigate the efficacy and action mechanisms of ISDF on psoriasis using imiquimod (IMQ) and Interleukin-23 (IL-23)-induced models in mice and reveal the pharmacokinetics profile of ISDF in rats. METHODS: Topical administration of IMQ and intradermal injection with IL-23 respectively induced skin lesions like psoriasis on the dorsal area of Balb/c and C57 mice. The mice's body weight, skin thickness, and psoriasis area and severity index (PASI) were assessed weekly. SD rats were used in the pharmacokinetics study and the contents of berberine and baicalin were determined. RESULTS: The PASI scores and epidermal thickness of mice were markedly decreased after ISDF treatment in both models. ISDF treatment significantly decreased the contents of IL-17A and IL-22 in the serum of IMQ- and IL-23-treated mice. Importantly, ISDF markedly downregulated IL-4, IL-6, IL-1ß, and tumor necrosis factor α (TNF-α) gene expression, and the phosphorylation of NF-κB p65, JNK, ERKs and MAPK p38 in IMQ-treated mice. The protein phosphorylation of Jak1, Jak2, Tyk2 and Stat3 was significantly mitigated in the ISDF-treated groups. The absorption of baicalin and berberine of ISDF through the gastrointestinal tract of rats was limited, and their distribution and metabolism in rats were also very slow, which suggested ISDF could be used in the long-term application. CONCLUSIONS: ISDF has a strong anti-psoriatic therapeutic effect on mouse models induced with psoriasis through IMQ and IL-23, which is achieved by inhibiting the activation of the Jak/Stat3-activated IL-23/Th17 axis and the downstream NF-κB signalling and MAPK signalling pathways. ISDF holds great potential to be a therapy for psoriasis and should be further developed for this purpose.

Which factors are associated with adverse prognosis in multiple myeloma patients after surgery? - preliminary establishment and validation of the nomogram.

BACKGROUND: To investigate the prognosis of patients with Multiple Myeloma (MM) after surgery, analyze the risk factors leading to adverse postoperative outcomes, and establish a nomogram. METHODS: Clinical data from 154 patients with MM who underwent surgery at our institution between 2007 and 2019 were retrospectively analyzed. Assessing and comparing patients' pain levels, quality of life, and functional status before and after surgery (P < 0.05) were considered statistically significant. The Kaplan-Meier survival curve was used to estimate the median survival time. Adverse postoperative outcomes were defined as worsened symptoms, lesion recurrence, complication grade ≥ 2, or a postoperative survival period < 1 year. Logistic regression analysis was used to determine the prognostic factors. Based on the logistic regression results, a nomogram predictive model was developed and calibrated. RESULTS: Postoperative pain was significantly alleviated in patients with MM, and there were significant improvements in the quality of life and functional status (P < 0.05). The median postoperative survival was 41 months. Forty-nine patients (31.8%) experienced adverse postoperative outcomes. Multivariate logistic regression analysis identified patient age, duration of MM, International Staging System, preoperative Karnofsky Performance Status, and Hb < 90 g/L as independent factors influencing patient prognosis. Based on these results, a nomogram was constructed, with a C-index of 0.812. The calibration curve demonstrated similarity between the predicted and actual survival curves. Decision curve analysis favored the predictive value of the model at high-risk thresholds from 10% to-69%. CONCLUSION: This study developed a nomogram risk prediction model to assist in providing quantifiable assessment indicators for preoperative evaluation of surgical risk.

Early administration of Wumei Wan inhibit myeloid-derived suppressor cells via PI3K/Akt pathway and amino acids metabolism to prevent colitis-associated colorectal cancer.

ETHNOPHARMACOLOGICAL RELEVANCE: Wumei Wan (WMW), a traditional Chinese medicine prescription, has been proved to be effective in treating Colitis-associated colorectal cancer (CAC), but it has not been proven to be effective in different stages of CAC. AIM OF THE STUDY: The purpose of our study is to investigate the therapeutic effect and mechanism of WMW on the progression of CAC. MATERIALS AND METHODS: Azioximethane (AOM) and dextran sulfate sodium (DSS) were used to treat mice for the purpose of establishing CAC models. WMW was administered in different stages of CAC. The presentative chemical components in WMW were confirmed by LC-MS/MS under the optimized conditions. The detection of inflammatory cytokines in the serum and colon of mice were estimated by qRT-PCR and ELISA. The changes of T cells and myeloid-derived suppressor cells (MDSCs) in each group were detected by flow cytometry. The metabolic components in serum of mice were detected by UPLC-MS/MS. Expression of genes and proteins were detected by eukaryotic transcriptomics and Western blot to explore the key pathway of WMW in preventing CAC. RESULTS: WMW had significant effect on inhibiting inflammatory responses and tumors during the early development stage of CAC when compared to other times. WMW increased the length of mice's colons, reduced the level of IL-1ß, IL-6, TNF-α in colon tissues, and effectively alleviated colonic inflammation, and improved the pathological damage of colon tissues. WMW could significantly reduce the infiltration of MDSCs in the spleen, increase CD4+ T cells and CD8+ T cells in the spleen of CAC mice, and effectively reform the immune microenvironment in CAC mice. Transcriptomics analysis revealed that 2204 genes had different patterns of overlap in the colon tissues of mice between control group, AOM + DSS group, and early administration of WMW group. And KEGG enrichment analysis showed that PI3K/Akt signaling pathway, ECM-receptor interaction, IL-17 signaling pathway, MAPK signaling pathway, pancreatic secretion, thermogenesis, and Rap1 signaling pathway were all involved. The serum metabolomics results of WMW showed that the metabolic compositions of the control group, AOM + DSS group and the early stage of WMW were different, and 42 differential metabolites with the opposite trends of changes were screened. The metabolic pathways mainly included pyrimidine metabolism, glycine, serine and threonine metabolism, tryptophan metabolism, and purine metabolism. And amino acids and related metabolites may play an important role in WMW prevention of CAC. CONCLUSION: WMW can effectively prevent the occurrence and development of CAC, especially in the initial stage. WMW can reduce the immune infiltration of MDSCs in the early stage. Early intervention of WMW can improve the metabolic disorder caused by AOM + DSS, especially correct the amino acid metabolism. PI3K/Akt signaling pathway was inhabited in early administration of WMW, which can regulate the amplification and function of MDSCs.

ASSIST-U: A system for segmentation and image style transfer for ureteroscopy.

Kidney stones require surgical removal when they grow too large to be broken up externally or to pass on their own. Upper tract urothelial carcinoma is also sometimes treated endoscopically in a similar procedure. These surgeries are difficult, particularly for trainees who often miss tumours, stones or stone fragments, requiring re-operation. Furthermore, there are no patient-specific simulators to facilitate training or standardized visualization tools for ureteroscopy despite its high prevalence. Here a system ASSIST-U is proposed to create realistic ureteroscopy images and videos solely using preoperative computerized tomography (CT) images to address these unmet needs. A 3D UNet model is trained to automatically segment CT images and construct 3D surfaces. These surfaces are then skeletonized for rendering. Finally, a style transfer model is trained using contrastive unpaired translation (CUT) to synthesize realistic ureteroscopy images. Cross validation on the CT segmentation model achieved a Dice score of 0.853 ± 0.084. CUT style transfer produced visually plausible images; the kernel inception distance to real ureteroscopy images was reduced from 0.198 (rendered) to 0.089 (synthesized). The entire pipeline from CT to synthesized ureteroscopy is also qualitatively demonstrated. The proposed ASSIST-U system shows promise for aiding surgeons in the visualization of kidney ureteroscopy.

Analysis of the efficacy of separation surgery for severe neurological compression in multiple myeloma: a retrospective analysis of 35 cases.

PURPOSE: To investigate the effectiveness and safety of separation surgery for Epidural Spinal Cord Compression (ESCC) graded ≥ 2 in patients with Multiple Myeloma (MM), analyze factors influencing surgical outcomes, and develop a preliminary treatment decision framework for these patients. METHODS: A retrospective analysis was conducted on clinical data from 35 MM patients who underwent separation surgery for ESCC graded ≥ 2 between 2013 and 2018. Patient data, including baseline information, surgical details, complications, and pre-operative as well as one-month post-operative efficacy evaluation indicators were recorded. Statistical analysis was performed on pre-operative and post-operative efficacy indicators to determine if there were significant improvements (p < 0.05). Ordered logistic regression was utilized to assess factors associated with an unfavorable post-operative quality of life outcome. RESULTS: Compared to pre-operative values, at one-month post-surgery, patients showed significant improvements in Frankel Score Classification (4 vs 5, p < 0.05), Karnofsky Performance Score (30 vs 70, p < 0.05), and Visual Analogue Scale (8 vs 3, p < 0.05). Complications occurred in 7 cases (20%). The number of segments with ESCC (OR = 0.171, p < 0.05) and pre-operative chemotherapy (OR = 5.202, p = 0.05) were identified as independent factors influencing patient outcomes. Patients with more than two vertebral segments with ESCC exhibited significantly worse post-operative conditions. CONCLUSIONS: Separation surgery effectively alleviates pain, improves neurological function, and enhances the quality of life in patients with ESCC graded ≥ 2 due to MM.

Objective Evaluation of Pulse Width Using an Array Pulse Diagram.

BACKGROUND: Pulse width, which can reflect qi, blood excess, and deficiency, has been used for diagnosing diseases and determining the prognosis in traditional Chinese medicine (TCM). This study aimed to devise an objective method to measure the pulse width based on an array pulse diagram for objective diagnosis. METHODS: The channel 6, the region wherein the pulse wave signal is the strongest, is located in the middle of the pulse sensor array and at the guan position of cunkou during data collection. Therefore, the main wave (h1) time of the pulse wave was collected from the channel 6 through calculation. The left h1 time was collected from the remaining 11 channels. The amplitudes at these time points were extracted as the h1 amplitudes for each channel. However, the pulse width could not be calculated accurately at 12 points. Consequently, a bioharmonic spline interpolation algorithm was used to interpolate the h1 amplitude data obtained from the horizontal and vertical points, yielding 651 (31 × 21) h1 amplitude data. The 651 data points were converted into a heat map to intuitively calculate the pulse width. The pulse width was calculated by multiplying the number of grids on the vertical axis with the unit length of the grid. The pulse width was determined by TCM doctors to verify the pulse width measurement accuracy. Meanwhile, a color Doppler ultrasound examination of the volunteers' radial arteries was performed and the intravascular meridian widths of the radial artery compared with the calculated pulse widths to determine the reliability. RESULTS: The pulse width determined using the maximal h1 amplitude method was comparable with the radial artery intravascular meridian widths measured using color Doppler ultrasound. The h1 amplitude was higher in the high blood pressure group and the pulse width was greater. CONCLUSIONS: The pulse width determined using the maximal h1 amplitude was objective and accurate. Comparison between the pulse widths of the normal and high blood pressure groups verified the reliability of the method.

Observation and quantification of the pseudogap in unitary Fermi gases.

The microscopic origin of high-temperature superconductivity in cuprates remains unknown. It is widely believed that substantial progress could be achieved by better understanding of the pseudogap phase, a normal non-superconducting state of cuprates1,2. In particular, a central issue is whether the pseudogap could originate from strong pairing fluctuations3. Unitary Fermi gases4,5, in which the pseudogap-if it exists-necessarily arises from many-body pairing, offer ideal quantum simulators to address this question. Here we report the observation of a pair-fluctuation-driven pseudogap in homogeneous unitary Fermi gases of lithium-6 atoms, by precisely measuring the fermion spectral function through momentum-resolved microwave spectroscopy and without spurious effects from final-state interactions. The temperature dependence of the pairing gap, inverse pair lifetime and single-particle scattering rate are quantitatively determined by analysing the spectra. We find a large pseudogap above the superfluid transition temperature. The inverse pair lifetime exhibits a thermally activated exponential behaviour, uncovering the microscopic virtual pair breaking and recombination mechanism. The obtained large, temperature-independent single-particle scattering rate is comparable with that set by the Planckian limit6. Our findings quantitatively characterize the pseudogap in strongly interacting Fermi gases and they lend support for the role of preformed pairing as a precursor to superfluidity.

Transcriptomic analyses and machine-learning methods reveal dysregulated key genes and potential pathogenesis in human osteoarthritic cartilage.

Aims: This study aimed to explore the biological and clinical importance of dysregulated key genes in osteoarthritis (OA) patients at the cartilage level to find potential biomarkers and targets for diagnosing and treating OA. Methods: Six sets of gene expression profiles were obtained from the Gene Expression Omnibus database. Differential expression analysis, weighted gene coexpression network analysis (WGCNA), and multiple machine-learning algorithms were used to screen crucial genes in osteoarthritic cartilage, and genome enrichment and functional annotation analyses were used to decipher the related categories of gene function. Single-sample gene set enrichment analysis was performed to analyze immune cell infiltration. Correlation analysis was used to explore the relationship among the hub genes and immune cells, as well as markers related to articular cartilage degradation and bone mineralization. Results: A total of 46 genes were obtained from the intersection of significantly upregulated genes in osteoarthritic cartilage and the key module genes screened by WGCNA. Functional annotation analysis revealed that these genes were closely related to pathological responses associated with OA, such as inflammation and immunity. Four key dysregulated genes (cartilage acidic protein 1 (CRTAC1), iodothyronine deiodinase 2 (DIO2), angiopoietin-related protein 2 (ANGPTL2), and MAGE family member D1 (MAGED1)) were identified after using machine-learning algorithms. These genes had high diagnostic value in both the training cohort and external validation cohort (receiver operating characteristic > 0.8). The upregulated expression of these hub genes in osteoarthritic cartilage signified higher levels of immune infiltration as well as the expression of metalloproteinases and mineralization markers, suggesting harmful biological alterations and indicating that these hub genes play an important role in the pathogenesis of OA. A competing endogenous RNA network was constructed to reveal the underlying post-transcriptional regulatory mechanisms. Conclusion: The current study explores and validates a dysregulated key gene set in osteoarthritic cartilage that is capable of accurately diagnosing OA and characterizing the biological alterations in osteoarthritic cartilage; this may become a promising indicator in clinical decision-making. This study indicates that dysregulated key genes play an important role in the development and progression of OA, and may be potential therapeutic targets.

The effect of the mitochondria-targeted antioxidant Mito-tempo during sperm ultra-rapid freezing.

During the freeze-thaw process, human spermatozoa are susceptible to oxidative stress, which may cause cryodamage and reduce sperm quality. As a novel mitochondria-targeted antioxidant, Mito-tempo has been used for sperm cryopreservation. However, it is currently unknown what role it will play in the process of sperm ultra-rapid freezing. The purpose of this study was to investigate whether Mito-tempo can improve sperm quality during ultra-rapid freezing. In this study, samples with the addition of Mito-tempo (0, 5, 10, 20, and 40 µM) to sperm freezing medium were selected to evaluate the changes in sperm quality, antioxidant capacity and ultrastructure after ultra-rapid freezing. After ultra-rapid freezing, the quality and antioxidant function of the spermatozoa were significantly reduced and the spermatozoa ultrastructure was destroyed. The addition of 10 µM Mito-tempo significantly increased post thaw sperm motility, viability, plasma membrane integrity and mitochondrial membrane potential (P < 0.05). Moreover, the DNA fragmentation index (DFI), ROS levels and MDA content were reduced, and the antioxidant enzyme (CAT and SOD) activities were enhanced in the 10 µM Mito-tempo group (P < 0.05). Moreover, Mito-tempo protected sperm ultrastructure from damage. In conclusion, Mito-tempo improved the quality and antioxidant function of sperm after ultra-rapid freezing while reducing freezing-induced ultrastructural damage.

Machine learning methods for the modelling and optimisation of biogas production from anaerobic digestion: a review.

Biogas plant operators often face huge challenges in the monitoring, controlling and optimisation of the anaerobic digestion (AD) process, as it is very sensitive to surrounding changes, which often leads to process failure and adversely affects biogas production. Conventional implemented methods and mechanistic models are impractical and find it difficult to model the nonlinear and intricate interactions of the AD process. Thus, the development of machine learning (ML) algorithms has attracted considerable interest in the areas of process optimization, real-time monitoring, perturbation detection and parameter prediction. This paper provides a comprehensive and up-to-date overview of different machine learning algorithms, including artificial neural network (ANN), fuzzy logic (FL), adaptive network-based fuzzy inference system (ANFIS), support vector machine (SVM), genetic algorithm (GA) and particle swarm optimization (PSO) in terms of working mechanism, structure, advantages and disadvantages, as well as their prediction performances in modelling the biogas production. A few recent case studies of their applications and limitations are also critically reviewed and compared, providing useful information and recommendation in the selection and application of different ML algorithms. This review shows that the prediction efficiency of different ML algorithms is greatly impacted by variations in the reactor configurations, operating conditions, influent characteristics, selection of input parameters and network architectures. It is recommended to incorporate mixed liquor volatile suspended solids (MLVSS) concentration of the anaerobic digester (ranging from 16,500 to 46,700 mg/L) as one of the input parameters to improve the prediction efficiency of ML modelling. This review also shows that the combination of different ML algorithms (i.e. hybrid GA-ANN model) could yield better accuracy with higher R2 (0.9986) than conventional algorithms and could improve the optimization model of AD. Besides, future works could be focused on the incorporation of an integrated digital twin system coupled with ML techniques into the existing Supervisory Control and Data Acquisition (SCADA) system of any biogas plant to detect any operational abnormalities and prevent digester upsets.

Comparison of biliary protein spectrum in gallstone patients with obesity and those with normal body weight.

BACKGROUND: Obesity is a common public health issue and is currently deemed a disease. Research has shown that the risk of gallstones in individuals with obesity is elevated. This study aimed to explore the bile proteomics differences between cholelithiasis patients with obesity and normal body weight. METHODS: Bile samples from 20 patients (10 with obesity and 10 with normal body weight) who underwent laparoscopic cholecystectomy at our center were subjected to tandem mass tag labeling (TMT) and liquid chromatography-tandem mass spectrometry (LC-MS/MS), followed by further bioinformatic analysis. RESULTS: Among the differentially-expressed proteins, 23 were upregulated and 67 were downregulated. Bioinformatic analysis indicated that these differentially-expressed proteins were mainly involved in cell development, inflammatory responses, glycerolipid metabolic processes, and protein activation cascades. In addition, the activity of the peroxisome proliferator-activated receptor (PPAR, a subfamily of nuclear receptors) signaling pathway was decreased in the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Two downregulated proteins in the PPAR signaling pathway, APOA-I and APOA-II, were confirmed using enzyme-linked immunosorbent assay. CONCLUSIONS: The PPAR signaling pathway may play a crucial role in the development of cholelithiasis among patients with obesity. Furthermore, biliary proteomics profiling of gallstones patients with obesity is revealed, providing a reference for future research.

Comparative physiological and transcriptomic analysis of two salt-tolerant soybean germplasms response to low phosphorus stress: role of phosphorus uptake and antioxidant capacity.

BACKGROUND: Phosphorus (P) and salt stress are common abiotic stressors that limit crop growth and development, but the response mechanism of soybean to low phosphorus (LP) and salt (S) combined stress remains unclear. RESULTS: In this study, two soybean germplasms with similar salt tolerance but contrasting P-efficiency, A74 (salt-tolerant and P-efficient) and A6 (salt-tolerant and P-inefficient), were selected as materials. By combining physiochemical and transcriptional analysis, we aimed to elucidate the mechanism by which soybean maintains high P-efficiency under salt stress. In total, 14,075 differentially expressed genes were identified through pairwise comparison. PageMan analysis subsequently revealed several significantly enriched categories in the LP vs. control (CK) or low phosphorus + salt (LPS) vs. S comparative combination when compared to A6, in the case of A74. These categories included genes involved in mitochondrial electron transport, secondary metabolism, stress, misc, transcription factors and transport. Additionally, weighted correlation network analysis identified two modules that were highly correlated with acid phosphatase and antioxidant enzyme activity. Citrate synthase gene (CS), acyl-coenzyme A oxidase4 gene (ACX), cytokinin dehydrogenase 7 gene (CKXs), and two-component response regulator ARR2 gene (ARR2) were identified as the most central hub genes in these two modules. CONCLUSION: In summary, we have pinpointed the gene categories responsible for the LP response variations between the two salt-tolerant germplasms, which are mainly related to antioxidant, and P uptake process. Further, the discovery of the hub genes layed the foundation for further exploration of the molecular mechanism of salt-tolerant and P-efficient in soybean.

Effect of Air Pollutants and Meteorological Factors on Daily Outpatient Visits of Allergic Rhinitis in Hohhot, China.

Objective: There is limited evidence that atmospheric pollutants are associated with the number of allergic rhinitis (AR) visits. This study aimed to investigate the relationship between atmospheric pollutants and meteorological factors and the number of daily visits for AR in Hohhot City, providing a theoretical basis for further research on the effects of atmospheric pollutants on AR. Methods: Microsoft Excel 2016 was used to collect and organize the AR outpatient consultation data, air pollution and meteorological data in Hohhot City during 2018-2020, and the data were descriptively analyzed and Spearman correlation test was performed using SPSS22.0; A generalized additive model was built in R4.2.3 to analyze the effect of air pollution on the number of AR visits and its lagged and cumulative effects, while the robustness of the model was tested using a two-pollutant analysis. Finally, we analyzed the effects of the interaction of temperature, relative humidity and pollutants on the number of AR visits. Results: The daily average concentrations of PM2.5, PM10, SO2, NO2, CO, and O3 in Hohhot during 2018-2020 were 38.1 µg/m3, 83.3 µg/m3, 36.1 µg/m3, 15.1 µg/m3, 14.2 mg/m3, and 99.95 µg/m3, respectively, with the concentrations of PM2.5 and PM10 exceeding the secondary limit of the national standard. The results of the generalized additive model analysis showed that the RR and 95% CI of the effect of each 10 µg/m3 increase in pollutant concentration (1 mg/m3 increase in CO) on the number of AR outpatient clinics were 1.008 (1.001-1.016), 1.002 (1-1.005), 1.072 (1.033-1.113), 1.020 (1007-1.034), 1.033 (1.014-1.052), 0.987 (0.9804-0.9936). Conclusion: Short-term exposure to PM2.5, PM10, SO2, NO2, and CO was significantly associated with an increase in AR clinic visits, and short-term exposure to O3 was significantly associated with a decrease in allergic rhinitis clinic visits.

Ecological Momentary Assessment of Midlife Adults' Daily Stress: Protocol for the Stress Reports in Variable Environments (STRIVE) App Study.

BACKGROUND: Daily stressors are associated with cognitive decline and increased risk of heart disease, depression, and other debilitating chronic illnesses in midlife adults. Daily stressors tend to occur at home or at work and are more frequent in urban versus rural settings. Conversely, spending time in natural environments such as parks or forests, or even viewing nature-themed images in a lab setting, is associated with lower levels of perceived stress and is hypothesized to be a strong stress "buffer," reducing perceived stress even after leaving the natural setting. However, many studies of daily stress have not captured environmental contexts and relied on end-of-day recall instead of in-the-moment data capture. With new technology, these limitations can be addressed to enhance knowledge of the daily stress experience. OBJECTIVE: We propose to use our novel custom-built Stress Reports in Variable Environments (STRIVE) ecological momentary assessment mobile phone app to measure the experience of daily stress of midlife adults in free-living conditions. Using our app to capture data in real time will allow us to determine (1) where and when daily stress occurs for midlife adults, (2) whether midlife adults' daily stressors are linked to certain elements of the built and natural environment, and (3) how ecological momentary assessment measurement of daily stress is similar to and different from a modified version of the popular Daily Inventory of Stressful Events measurement tool that captures end-of-day stress reports (used in the Midlife in the United States [MIDUS] survey). METHODS: We will enroll a total of 150 midlife adults living in greater Indianapolis, Indiana, in this study on a rolling basis for 3-week periods. As those in underrepresented minority groups and low-income areas have previously been found to experience greater levels of stress, we will use stratified sampling to ensure that half of our study sample is composed of underrepresented minorities (eg, Black, American Indian, Hispanic, or Native Pacific Islanders) and approximately one-third of our sample falls within low-, middle-, and high-income brackets. RESULTS: This project is funded by the National Institute on Aging from December 2022 to November 2024. Participant enrollment began in August 2023 and is expected to finish in July 2024. Data will be spatiotemporally analyzed to determine where and when stress occurs for midlife adults. Pictures of stressful environments will be qualitatively analyzed to determine the common elements of stressful environments. Data collected by the STRIVE app will be compared with retrospective Daily Inventory of Stressful Events data. CONCLUSIONS: Completing this study will expand our understanding of midlife adults' experience of stress in free-living conditions and pave the way for data-driven individual and community-based intervention designs to promote health and well-being in midlife adults. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/51845.

Case report: Giant atypical granular cell tumor of the median nerve.

Granular cell tumors are extremely uncommon soft tissue neoplasms that mostly occur in the head and neck regions. Granular cell tumors are generally benign, asymptomatic, and rarely involve the median nerve. Due to the lack of awareness about granular cell tumors, they are easily misdiagnosed and mistreated in primary hospitals. Here, we report a giant atypical granular cell tumor located on the median nerve, approximately 12 cm in size, with unusual symptoms of median nerve damage. Magnetic resonance imaging revealed a fusiform mass that was hyperintense on T2-weighted images and iso-hypointense on T1-weighted images. The mass was subsequently biopsied and found to be a granular cell tumor. The tumor was resected, and a pathological examination was performed. Pathological examination revealed necrotic foci, abundant eosinophilic granules, pustular ovoid bodies, and multiple mitoses. Immunohistochemical staining revealed that the tumor cells were positive for S-100, CD68, SMA, SOX-10, Calretinin, and TFE3. The integrated diagnosis was an atypical granular cell tumor. To the best of our knowledge, this is the first report of an atypical granular cell tumor involving the median nerve. Furthermore, we comprehensively reviewed the existing literature to provide a concise summary of the diagnostic criteria, imaging findings, and pathological features of granular cell tumors. Given the high recurrence and metastasis rates of this disease, granular cell tumors of the median nerve should be considered when a patient presents with symptoms of median nerve impairment. The diagnosis of atypical granular cell tumors relies on pathological examination. In addition, extensive resection and long-term follow-up are necessary to improve prognosis.

Contribution identification of hydrolyzed products of potassium ferrate on promoting short-chain fatty acids production from waste activated sludge.

Potassium ferrate (K2FeO4) has been extensively employed to promote short-chain fatty acids (SCFAs) production from anaerobic fermentation of waste activated sludge (WAS) because of its potent oxidizing property and formation of alkaline hydrolyzed products (potassium hydroxide, KOH and ferric hydroxide, Fe(OH)3). However, whether K2FeO4 actually works as dual functions of both an oxidizing agent and an alkalinity enhancer during the anaerobic fermentation process remains uncertain. This study aims to identify the contributions of hydrolyzed products of K2FeO4 on SCFAs production. The results showed that K2FeO4 did not execute dual functions of oxidization and alkalinity in promoting SCFAs production. The accumulation of SCFAs using K2FeO4 treatment (183 mg COD/g volatile suspended solids, VSS) was less than that using either KOH (192 mg COD/g VSS) or KOH & Fe(OH)3 (210 mg COD/g VSS). The mechanism analysis indicated that the synergistic effects caused by oxidization and alkalinity properties of K2FeO4 did not happen on solubilization, hydrolysis, and acidogenesis stages, and the inhibition effect caused by K2FeO4 on methanogenesis stage at the initial phase was more severe than that of its hydrolyzed products. It was also noted that the inhibition effects of K2FeO4 and its hydrolyzed products on the methanogenesis stage could be relieved during a longer sludge retention time, and the final methane yields using KOH or KOH & Fe(OH)3 treatment were higher than that using K2FeO4, further confirming that dual functions of K2FeO4 were not obtained. Therefore, K2FeO4 may not be an alternative strategy for enhancing the production of SCFAs from WAS compared to its alkaline hydrolyzed products. Regarding the strong oxidization property of K2FeO4, more attention could be turned to the fates of refractory organics in the anaerobic fermentation of WAS.

Learning curve of tibial cortex transverse transport: a cumulative sum analysis.

OBJECTIVE: This study aimed to describe the learning curve of surgeons performing tibial cortex transverse transport (TTT) and explore its safety and effectiveness during the initial stages of surgeon's learning. METHODS: The clinical data of patients with diabetic foot ulcers classified as Wagner grade ≥ 2, who underwent TTT at our hospital from January 2020 to July 2021, were included in this retrospective analysis. The same physician performed all procedures. Patients were numbered according to the chronological order of their surgery dates. The cumulative sum and piecewise linear regression were used to evaluate the surgeon's learning curve, identify the cut-off point, and divide the patients into learning and mastery groups. A minimum follow-up period of 3 months was ensured for all patients. Baseline data, perioperative parameters, complications, and efficacy evaluation indicators were recorded and compared between the two groups. RESULTS: Sixty patients were included in this study based on the inclusion and exclusion criteria. After completing 20 TTT surgeries, the surgeon reached the cut-off point of the learning curve. Compared to the learning group, the mastery group demonstrated a significant reduction in the average duration of the surgical procedure (34.88 min vs. 54.20 min, P < 0.05) along with a notable decrease in intraoperative fluoroscopy (9.75 times vs. 16.9 times, P < 0.05) frequency, while no significant difference was found regarding intraoperative blood loss (P = 0.318). Of the patients, seven (11.7%) experienced complications, with three (15%) and four cases (10%) occurring during the learning phase and the mastery phase, respectively. The postoperative ulcer area was significantly reduced, and the overall healing rate was 94.8%. Significant improvements were observed in postoperative VAS, ABI, and WIFI classification (P < 0.05). There were no significant differences in the occurrence of complications or efficacy indicators between the learning and mastery groups (P > 0.05). CONCLUSION: Surgeons can master TTT after completing approximately 20 procedures. TTT is easy, secure, and highly efficient for treating foot ulcers. Furthermore, TTT's application by surgeons can achieve almost consistent clinical outcomes in the initial implementation stages, comparable to the mastery phase.

Structural and functional network analysis of twins using fMRI data.

Similarities between twins have been widely demonstrated, underscoring the remarkable influence of genetics across numerous traits. In this study, we explore the genetic underpinnings of the human brain by examining MRI data from the Queensland Twin Imaging study. Specifically, this study seeks to compare brain structure and function between twins and unrelated subjects, with an emphasis on describing the effects of genetic factors. To achieve these goals, we employed the source-based morphometry method to extract intrinsic components and elucidate recognizable patterns. Our results show that twins exhibit a higher degree of similarity in gray and white matter density compared with unrelated individuals. In addition, four distinct states of brain activity were identified using coactivation patterns analysis. Furthermore, twins demonstrated a greater degree of similarity in the temporal and spatial features of each state compared with unrelated subjects. Taken together, these results support the hypothesis that twins show greater similarity in both brain structure and dynamic functional brain activity. Further exploration of these methods may advance our understanding of the complex interplay between genes, environment, and brain networks.