Highly reversible Zn anodes enabled by in-situ construction of zincophilic zinc polyacrylate interphase for aqueous Zn-ion batteries.

The irreversibility and low utilization of Zn anode stemming from the corrosion and dendrite growth have largely limited the commercialization of aqueous zinc batteries. Here, a carbonyl-rich polymer interphase of zinc polyacrylate (ZPAA) is spontaneously in-situ constructed on Zn anode to address the above-mentioned dilemmas. The ZPAA interlayer enables fast transport kinetics of Zn2+ and tailors the interfacial electric field for realizing the uniform Zn deposition due to superior zincophilicity, high Zn2+ transference number and inherent ion-diffusion channel. Importantly, acting as a buffer interphase with strong adhesion and isolation of electrolytes, this functional layer effectively protects the Zn electrode against the water-induced erosion and passivation. Remarkably, the ZPAA@Zn electrode realizes an enhanced Coulombic efficiency of 99.71 % within 2200 cycles, delivers an ultra-long cycling stability over 7660 h (>319 days, 1 mA cm-2) and 2460 h (5 mA cm-2) with lower voltage hysteresis. Also, the ZPAA@Zn/MnO2 full cell maintains a high capacity of 114 mAh/g after 2000 cycles, much better that of untreated Zn/MnO2 cell (25 mAh/g). This concept of in-situ fabricating ion-sieve-like polymer interphase provides a facile approach to stabilize Zn anode and further paves a way for high-performance aqueous batteries.

Ionic liquid-integrated aqueous electrolyte regulation on solvation chemistry and electrode interface for reversible dendrite-free zinc anodes.

Zn anodes suffer from poor reversibility and stability owing to nonuniform dendrite growth and self-corrosion. Here, 1-ethyl-3-methylimidazolium acetate (EMImAc) is introduced to reconstruct interfacial electrical double layer with simultaneously manipulating the solvation environment and the adsorption situation on Zn anode. The acetate anions with high nucleophilicity can effectively alter the solvation shell around Zn2+ ions and immobilize the H2O molecules, thus weakening water activity and alleviating water-related parasitic reactions. Concomitantly, both the imidazolium cation and acetate anion are inclined to gather on Zn anode surface for constructing an electrostatic shielding layer, and meanwhile the chemisorbed acetate anions also contribute to accelerate the Zn(H2O)62+ desolvation process. Such a synergistic effect enables uniform electric field distribution and facilitates Zn ion flux, which mitigates the random diffusion of Zn2+ and finally promotes the dendrite-free deposition. As a result, the Zn/Zn symmetric cells with EMImAc-integrated aqueous electrolyte realize an excellent cycling lifespan of 7000 h (0.5 mA cm-2/0.25 mAh cm-2) and high Zn utilization of 61.3 % (15 mA cm-2/20 mAh cm-2). Furthermore, the effective of EMImAc additive is demonstrated in Zn/V2O5 cells. This work offers insights into the ionic liquid-integrated aqueous electrolytes to enhance the interface stability of Zn anode for rechargeable zinc batteries.

In-situ synthesis to promote surface reconstruction of metal-organic frameworks for high-performance water/seawater oxidation.

Metal-organic frameworks (MOFs) have gained tremendous notice for the application in alkaline water/seawater oxidation due to their tunable structures and abundant accessible metal sites. However, exploring cost-effective oxygen evolution reaction (OER) electrocatalysts with high catalytic activity and excellent stability remains a great challenge. In this work, a promising strategy is proposed to regulate the crystalline structures and electronic properties of NiFe-metal-organic frameworks (NiFe-MOFs) by altering the organic ligands. As a representative sample, NiFe-BDC (BDC: C8H6O4) synthesized on nickel foam (NF) shows extraordinary OER activity in alkaline condition, delivering ultralow overpotentials of 204, 234 and 273 mV at 10, 100, and 300 mA cm-2, respectively, with a small Tafel slope of 21.6 mV dec-1. Only a slight decrease is observed when operating in alkaline seawater. The potential attenuation is barely identified at 200 mA cm-2 over 200 h continuous test, indicating the remarkable stability and corrosion resistance. In-situ measurements indicate that initial Ni2+/Fe2+ goes through oxidation process into Ni3+/Fe3+ during OER, and eventually presents in the form of NiFeOOH/NiFe-BDC heterojunction. The unique self-reconstructed surface is responsible for the low reaction barrier and fast reaction kinetics. This work provides an effective strategy to develop efficient MOF-based electrocatalysts and an insightful view on the dynamic structural evolution during OER.

Coal-derived boron and phosphorus co-doped activated carbon with expanded interlayer space for high performance sodium ion capacitor anode.

Aiming at the key problem of Na+ insertion difficulty and low charge transfer efficiency of activated carbon materials. It is an effective strategy to increase the lattice spacing and defect concentration by doping to reduce the ion diffusion resistance and improve the kinetics. Hence, anthracitic coal is used to prepare activated carbon (AC) and B,P-doped activated carbon (B,P-AC) as the cathode and anode materials for high-performance all-carbon SICs, respectively. AC cathode material has high specific surface area and reasonable micropore structure, which shows excellent capacitance performance. B,P-AC anode material has the advantages of extremely high specific surface area (1856.1 m2/g), expanded interlayer spacing (0.40 nm) and uniform distribution of B and P heteroatoms. Hence, B,P-AC anode achieves a highly reversible Na+ storage capacity of 243 mAh/g at a current density of 0.05 A/g. Density functional theory (DFT) calculations further verify that B,P-AC has stronger Na+ storage performance. The final assembled B,P-AC//AC SIC offers a high energy density of 109.78 Wh kg-1 and a high-power density of 10.03 kW kg-1. The high-performance coal-derived activated carbon of this work provides a variety of options for industrial production of electrode materials for sodium ion capacitors.

A Paradoxical Tumor Antigen Specific Response in the Liver.

Functional tumor-specific CD8+ T cells are essential for an effective anti-tumor immune response and the efficacy of immune checkpoint inhibitor therapy. In comparison to other organ sites, we found higher numbers of tumor-specific CD8+ T cells in primary, metastatic liver tumors in murine tumor models. Despite their abundance, CD8+ T cells in the liver displayed an exhausted phenotype. Depletion of CD8+ T cells showed that liver tumor-reactive CD8+ T failed to control liver tumors but was effective against subcutaneous tumors. Similarly, analysis of single-cell RNA sequencing data from patients showed a higher frequency of exhausted tumor-reactive CD8+ T cells in liver metastasis compared to paired primary colon cancer. High-dimensional, multi-omic analysis combining proteomic CODEX and scRNA-seq data revealed enriched interaction of SPP1+ macrophages and CD8+ tumor-reactive T cells in profibrotic, alpha-SMA rich regions in the liver. Liver tumors grew less in Spp1-/- mice and the tumor-specific CD8+ T cells were less exhausted. Differential pseudotime trajectory inference analysis revealed extrahepatic signaling promoting an intermediate cell (IC) population in the liver, characterized by co-expression of VISG4, CSF1R, CD163, TGF-ßR, IL-6R, SPP1. scRNA-seq of a third data set of premetastatic adenocarcinoma showed that enrichment of this population may predict liver metastasis. Our data suggests a mechanism by which extrahepatic tumors facilitate the formation of liver metastasis by promoting an IC population inhibiting tumor-reactive CD8+ T cell function.

PepCA: Unveiling protein-peptide interaction sites with a multi-input neural network model.

The protein-peptide interaction plays a pivotal role in fields such as drug development, yet remains underexplored experimentally and challenging to model computationally. Herein, we introduce PepCA, a sequence-based approach for predicting peptide-binding sites on proteins. A primary obstacle in predicting peptide-protein interactions is the difficulty in acquiring precise protein structures, coupled with the uncertainty of polypeptide configurations. To address this, we first encode protein sequences using the Evolutionary Scale Modeling 2 (ESM-2) pre-trained model to extract latent structural information. Additionally, we have developed a multi-input coattention mechanism to concurrently update the encoding of both peptide and protein residues. PepCA integrates this module within an encoder-decoder structure. This model's high precision in identifying binding sites significantly advances the field of computational biology, offering vital insights for peptide drug development and protein science.

Tumor microbiota of renal cell carcinoma affects clinical prognosis by influencing the tumor immune microenvironment.

Despite reported influences of the intratumoral microbiome on cancer progression, its role in this subtype remains unclear. This study aimed to characterize the microbial landscape and signatures of kidney renal clear cell carcinoma using RNA-Seq data from The Cancer Genome Atlas. Following microbial decontamination, differential microbial analysis was conducted between tumorous and adjacent non-tumorous samples. Compared to non-tumorous samples, tumorous microbiota exhibited reduced α and ß diversity and distinct phylum-level communities. Differential microbial analysis between patients exhibiting long and short overall survival revealed ten significant differential microbial genera, with six genera correlating with a positive prognosis (Plasmodium, Babesia, Toxoplasma, Cytobacillus, Alicyclobacillus, Verrucomicrobium) and four with a negative prognosis (Colletotrichum, Leuconostoc, Gluconobacter, and Parabacteroides). Employing Cox regression analysis and support vector machines, a prognosis-related microbiome risk signature was developed, achieving an AUC of 0.809. Based on this risk signature, two microbiome-based subtypes were found to be significantly associated with distinct clinical prognoses and immune microenvironments. These findings were corroborated by significant correlations between prognostic-relevant microorganisms and 30 immune-related differentially expressed genes. Specifically, microbial genera associated with a negative prognosis were linked to a pro-tumor acute inflammatory immune response, whereas genera related to a positive prognosis were associated with an anti-tumor adaptive immune response. In conclusion, microbiome-based subtyping revealed correlations between tumor microbiome, clinical prognosis, and tumor microenvironment, indicating intratumoral microbiota as a promising prognostic biomarker for kidney renal clear cell carcinoma.

A Review of the Occurrence and Recovery of Rare Earth Elements from Electronic Waste.

Electronic waste (e-waste) contains valuable rare earth elements (REEs) essential for various high-tech applications, making their recovery crucial for sustainable resource management. This review provides an overview of the occurrence of REEs in e-waste and discusses both conventional and emerging green technologies for their recovery. Conventional methods include physical separation, hydrometallurgy, and pyrometallurgy, while innovative approaches such as bioleaching, supercritical fluid extraction, ionic liquid extraction, and lanmodulin-derived peptides offer improved environmental sustainability and efficiency. The article presents case studies on the extraction of REEs from waste permanent magnets and fluorescent powders, highlighting the specific processes involved. Future research should focus on developing eco-friendly leaching agents, separation materials, and process optimization to enhance the overall sustainability and efficiency of REE recovery from e-waste, addressing both resource recovery and environmental concerns effectively.

Robust Strain Sensor with High Sensitivity Based on Polymer-Encapsulated Microfiber Mach-Zehnder Interferometer.

A robust strain sensor is demonstrated based on a microfiber Mach-Zehnder interferometer (MMZI) encapsulated by the polymer polydimethylsiloxane (PDMS). Benefiting from the low Young's modulus of PDMS, both a robust structure and high sensitivity can be realized based on three different encapsulations. In the experiment, the proposed sensors are fabricated and tested with strain sensitivities ranging from -20.95 pm/µÎµ to 127.00 pm/µÎµ within the wavelength range of 1200-1650 nm. Compared with the bare MMZI sensor, at least one order of magnitude higher sensitivity is reached. To further evaluate the performance of the sensor, the dependences of sensitivity on probing wavelength and the different types and quantities of polymers used in encapsulation are discussed. Results show that the sensitivity of the sensor will increase with the probing wavelength. The type and quantity of polymer used are also very critical to sensitivity. Additionally, a response time of 24.72 ms can be reached. Good recoverability and repeatability of the sensor are also demonstrated by repeated experiments. The strain sensor demonstrated here shows the advantages of simple fabrication, robust structure, high and tunable sensitivity, fast response, good recoverability and repeatability.

Peroxynitrite scavenger FeTPPS binds with hCT to effectively inhibit its amyloid aggregation.

Human calcitonin (hCT) is an endogenous polypeptide commonly employed in treating bone resorption-related illnesses, but its clinical application is limited due to its high aggregation tendency. Metalloporphyrins are effective in suppressing amyloid fibrillation, positioning them as potential drug candidates for amyloidogenic disorders like Alzheimer's and type 2 diabetes. In this work, we investigated the effects of Fe(III) meso-tetra(4-sulfonatophenyl)porphine chloride (FeTPPS), a highly efficient ONOO- decomposition catalyst, on hCT aggregation. Our findings reveal that FeTPPS effectively precludes hCT fibrillation by stabilizing the monomers and delaying the structural transition from α-helix bundles to ß-sheet-rich aggregates. The macrocyclic ring of FeTPPS plays a significant role in disrupting hCT self-associations. Among various porphyrin analogs, those with an iron center and negatively charged peripheral substituents exhibit a stronger inhibitory effect on hCT aggregation. Spectroscopic analyses and computational simulations indicate that FeTPPS binds to hCT's core aggregation region via complexation with His20 in a 1 : 1 molar ratio. Hydrophobic interaction, hydrogen bonding, and π-π stacking with the residues involving Tyr12, Phe19, and Ala26 also contribute to the interactions. Collectively, our study provides a promising approach for developing novel hCT drug formulations and offers theoretical guidance for designing metalloporphyrin-based inhibitors for various amyloidosis conditions.

Modelling of enhanced gas extraction in low permeability coal seam by controllable shock wave fracturing.

The controlled shock wave (CSW) fracturing is an effective method for enhancing permeability of coal seam to promote gas extraction. Based on Fick's law, Darcy's law, the ideal gas law and the Langmuir equation, a damage-seepage-deformation coupling mathematical model of CSW fracturing in coal seam combined with the maximum tensile stress and the Mohr-Coulomb criterion is established. This model is implemented into COMSOL Multiphysics to simulate the coal seam CSW fracturing and subsequent gas extraction. When the shock wave and isotropic in-situ stress are applied on the borehole wall, the coal damage zone is an annular shape, and the permeability in the damage zone increases sharply. The CSW can effectively increase the efficiency of gas extraction and reduce the gas pressure and gas content in coal seam. With the increase of CSW action times, the damage in coal mass reaches a threshold and tends to be stable after several shocks. The damage area and the gas extraction efficiency are positively correlated with the shock intensity. Under the anisotropic ground stress, the larger diversity of the stress in different directions is, the more obvious damage extension in the fractured coal along the maximum stress direction is. Ground stress can inhibit the extension of cracks in the CSW fractured coal seam. This inhibition effect becomes more obvious with the increase of in-situ stress. Parameters are substantiated of controlled shock wave impact on the coal seam, which ensures increased methane extraction from low-permeability reservoirs, are substantiated.

Association between composite dietary antioxidant index and migraine in American young women: insights from NHANES 1999-2004 cross-sectional data.

Background: Excessive oxidative stress is one of the key pathophysiological mechanisms underlying migraine, and increasing antioxidant intake has proven to be an effective strategy for the prevention and improvement of migraine symptoms. To explore the relationship between the composite dietary antioxidant index (CDAI) and the occurrence of migraine attacks. Methods: Cross-sectional data from the National Health and Nutrition Examination Survey (NHANES) spanning 1999-2004 were utilized. Logistic regression, stratified analysis, and restricted cubic spline (RCS) models were employed to investigate the association between CDAI and migraine attacks. Results: A total of 8,137 adults aged ≥20 were enrolled, comprising 1,610 patients with migraine and 6,527 non-migraine individuals. After adjusting for all covariates, CDAI was negatively correlated with migraine. In the overall participants, compared with the CDAI Q1 (-5.83 to -2.14) group, the adjusted odds ratio (OR) for migraine in Q3 (-0.59 to 1.53) and Q4 (1.53-44.63) groups were 0.71 [95% confidence interval (95% CI): 0.54-0.92, p = 0.011] and 0.64 (95% CI: 0.47-0.87, p = 0.005), respectively. After stratifying by age and gender, the protective effect was more pronounced in females aged 20-50, with adjusted OR for Q3 (-0.59 to 1.53) and Q4 (1.53-44.63) groups of 0.60 (95% CI: 0.40-0.90, p = 0.013) and 0.48 (95% CI: 0.30-0.78, p = 0.003), respectively. The RCS curve indicated a nonlinear relationship between CDAI and migraine in females aged 20-50, with a threshold of 0.006. Conclusion: CDAI is negatively correlated with migraine attacks, and a higher CDAI may be an effective protective factor in preventing migraine attacks, especially in women aged 20-50.

Highly sensitive detection platform-based diagnosis of oesophageal squamous cell carcinoma in China: a multicentre, case-control, diagnostic study.

BACKGROUND: Early detection and screening of oesophageal squamous cell carcinoma rely on upper gastrointestinal endoscopy, which is not feasible for population-wide implementation. Tumour marker-based blood tests offer a potential alternative. However, the sensitivity of current clinical protein detection technologies is inadequate for identifying low-abundance circulating tumour biomarkers, leading to poor discrimination between individuals with and without cancer. We aimed to develop a highly sensitive blood test tool to improve detection of oesophageal squamous cell carcinoma. METHODS: We designed a detection platform named SENSORS and validated its effectiveness by comparing its performance in detecting the selected serological biomarkers MMP13 and SCC against ELISA and electrochemiluminescence immunoassay (ECLIA). We then developed a SENSORS-based oesophageal squamous cell carcinoma adjunct diagnostic system (with potential applications in screening and triage under clinical supervision) to classify individuals with oesophageal squamous cell carcinoma and healthy controls in a retrospective study including participants (cohort I) from Sun Yat-sen University Cancer Center (SYSUCC; Guangzhou, China), Henan Cancer Hospital (HNCH; Zhengzhou, China), and Cancer Hospital of Shantou University Medical College (CHSUMC; Shantou, China). The inclusion criteria were age 18 years or older, pathologically confirmed primary oesophageal squamous cell carcinoma, and no cancer treatments before serum sample collection. Participants without oesophageal-related diseases were recruited from the health examination department as the control group. The SENSORS-based diagnostic system is based on a multivariable logistic regression model that uses the detection values of SENSORS as the input and outputs a risk score for the predicted likelihood of oesophageal squamous cell carcinoma. We further evaluated the clinical utility of the system in an independent prospective multicentre study with different participants selected from the same three institutions. Patients with newly diagnosed oesophageal-related diseases without previous cancer treatment were enrolled. The inclusion criteria for healthy controls were no obvious abnormalities in routine blood and tumour marker tests, no oesophageal-associated diseases, and no history of cancer. Finally, we assessed whether classification could be improved by integrating machine-learning algorithms with the system, which combined baseline clinical characteristics, epidemiological risk factors, and serological tumour marker concentrations. Retrospective SYSUCC cohort I (randomly assigned [7:3] to a training set and an internal validation set) and three prospective validation sets (SYSUCC cohort II [internal validation], HNCH cohort II [external validation], and CHSUMC cohort II [external validation]) were used in this step. Six machine-learning algorithms were compared (the least absolute shrinkage and selector operator regression, ridge regression, random forest, logistic regression, support vector machine, and neural network), and the best-performing algorithm was chosen as the final prediction model. Performance of SENSORS and the SENSORS-based diagnostic system was primarily assessed using accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). FINDINGS: Between Oct 1, 2017, and April 30, 2020, 1051 participants were included in the retrospective study. In the prospective diagnostic study, 924 participants were included from April 2, 2022, to Feb 2, 2023. Compared with ELISA (108·90 pg/mL) and ECLIA (41·79 pg/mL), SENSORS (243·03 fg/mL) showed 448 times and 172 times improvements, respectively. In the three retrospective validation sets, the SENSORS-based diagnostic system achieved AUCs of 0·95 (95% CI 0·90-0·99) in the SYSUCC internal validation set, 0·93 (0·89-0·97) in the HNCH external validation set, and 0·98 (0·97-1·00) in the CHSUMC external validation set, sensitivities of 87·1% (79·3-92·3), 98·6% (94·4-99·8), and 93·5% (88·1-96·7), and specificities of 88·9% (75·2-95·8), 74·6% (61·3-84·6), and 92·1% (81·7-97·0), respectively, successfully distinguishing between patients with oesophageal squamous cell carcinoma and healthy controls. Additionally, in three prospective validation cohorts, it yielded sensitivities of 90·9% (95% CI 86·1-94·2) for SYSUCC, 84·8% (76·1-90·8) for HNCH, and 95·2% (85·6-98·7) for CHSUMC. Of the six machine-learning algorithms compared, the random forest model showed the best performance. A feature selection step identified five features to have the highest performance to predictions (SCC, age, MMP13, CEA, and NSE) and a simplified random forest model using these five features further improved classification, achieving sensitivities of 98·2% (95% CI 93·2-99·7) in the internal validation set from retrospective SYSUCC cohort I, 94·1% (89·9-96·7) in SYSUCC prospective cohort II, 88·6% (80·5-93·7) in HNCH prospective cohort II, and 98·4% (90·2-99·9) in CHSUMC prospective cohort II. INTERPRETATION: The SENSORS system facilitates highly sensitive detection of oesophageal squamous cell carcinoma tumour biomarkers, overcoming the limitations of detecting low-abundance circulating proteins, and could substantially improve oesophageal squamous cell carcinoma diagnostics. This method could act as a minimally invasive screening tool, potentially reducing the need for unnecessary endoscopies. FUNDING: The National Key R&D Program of China, the National Natural Science Foundation of China, and the Enterprises Joint Fund-Key Program of Guangdong Province. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

Trends in 5-year cancer survival disparities by race and ethnicity in the US between 2002-2006 and 2015-2019.

Racial and ethnic disparities persist in cancer survival rates across the United States, despite overall improvements. This comprehensive analysis examines trends in 5-year relative survival rates from 2002-2006 to 2015-2019 for major cancer types, elucidating differences among racial/ethnic groups to guide equitable healthcare strategies. Data from the SEER Program spanning 2000-2020 were analyzed, focusing on breast, colorectal, prostate, lung, pancreatic cancers, non-Hodgkin lymphoma, acute leukemia, and multiple myeloma. Age-standardized relative survival rates were calculated to assess racial (White, Black, American Indian/Alaska Native, Asian/Pacific Islander) and ethnic (Hispanic, Non-Hispanic) disparities, utilizing period analysis for recent estimates and excluding cases identified solely through autopsy or death certificates. While significant survival improvements were observed for most cancers, notable disparities persisted. Non-Hispanic Blacks exhibited the largest gain in breast cancer survival, with an increase of 5.2% points (from 77.6 to 82.8%); however, the survival rate remained lower than that of Non-Hispanic Whites (92.1%). Colorectal cancer survival declined overall (64.7-64.1%), marked by a 6.2% point drop for Non-Hispanic American Indian/Alaska Natives (66.3-60.1%). Prostate cancer survival declined across all races, with Non-Hispanic American Indian/Alaska Natives showing a decrease of 7.7% points (from 96.9 to 89.2%). Lung cancer, acute leukemia, and multiple myeloma showed notable increases across groups. Substantial racial/ethnic disparities in cancer survival underscore the notable need for tailored strategies ensuring equitable access to advanced treatments, particularly addressing significant trends in colorectal and pancreatic cancers among specific minority groups. Careful interpretation of statistical significance is warranted given the large dataset.

Boundary-Aware Prototype in Semi-Supervised Medical Image Segmentation.

The true label plays an important role in semi-supervised medical image segmentation (SSMIS) because it can provide the most accurate supervision information when the label is limited. The popular SSMIS method trains labeled and unlabeled data separately, and the unlabeled data cannot be directly supervised by the true label. This limits the contribution of labels to model training. Is there an interactive mechanism that can break the separation between two types of data training to maximize the utilization of true labels? Inspired by this, we propose a novel consistency learning framework based on the non-parametric distance metric of boundary-aware prototypes to alleviate this problem. This method combines CNN-based linear classification and nearest neighbor-based non-parametric classification into one framework, encouraging the two segmentation paradigms to have similar predictions for the same input. More importantly, the prototype can be clustered from both labeled and unlabeled data features so that it can be seen as a bridge for interactive training between labeled and unlabeled data. When the prototype-based prediction is supervised by the true label, the supervisory signal can simultaneously affect the feature extraction process of both data. In addition, boundary-aware prototypes can explicitly model the differences in boundaries and centers of adjacent categories, so pixel-prototype contrastive learning is introduced to further improve the discriminability of features and make them more suitable for non-parametric distance measurement. Experiments show that although our method uses a modified lightweight UNet as the backbone, it outperforms the comparison method using a 3D VNet with more parameters.

High-Entropy Materials for Application: Electricity, Magnetism, and Optics.

High-entropy materials (HEMs) have recently emerged as a prominent research focus in materials science, gaining considerable attention because of their complex composition and exceptional properties. These materials typically comprise five or more elements mixed approximately in equal atomic ratios. The resultant high-entropy effects, lattice distortions, slow diffusion, and cocktail effects contribute to their unique physical, chemical, and optical properties. This study reviews the electrical, magnetic, and optical properties of HEMs and explores their potential applications. Additionally, it discusses the theoretical calculation methods and preparation techniques for HEMs, thereby offering insights and prospects for their future development.

Uterine tumor resembling ovarian sex cord tumor: A case report.

We report a case of a 65-year-old postmenopausal female patient who presented with 1 day of vaginal bleeding. Imaging studies diagnosed a uterine tumor lesion, and the patient underwent a total hysterectomy and bilateral salpingo-oophorectomy. The excised specimen was sent for pathological examination, and based on immunohistochemical analysis, the patient was ultimately diagnosed with Uterine tumor resembling ovarian sex cord tumor (UTROSCT). Postoperative adjuvant chemotherapy was administered, and the patient has been in good condition during the follow-up period.

Primary vaginal malignant melanoma: A case report.

Malignant melanoma is a rare malignant tumor that can occur in many parts of the body. Primary vaginal malignant melanoma (PVMM) in women accounts for only 3%-7% of all malignant melanomas. PVMM is extremely rare, aggressive, and has a poor prognosis. We report a case of primary vaginal malignant melanoma in order to improve our understanding of the disease.

Navigating therapeutic challenges in VEXAS syndrome: exploring IL-6 and JAK inhibitors at the forefront.

VEXAS syndrome, an uncommon yet severe autoimmune disorder stemming from a mutation in the UBA1 gene, is the focus of this paper. The overview encompasses its discovery, epidemiological traits, genetic underpinnings, and clinical presentations. Delving into whether distinct genotypes yield varied clinical phenotypes in VEXAS patients, and the consequent adjustment of treatment strategies based on genotypic and clinical profiles necessitates thorough exploration within the clinical realm. Additionally, the current therapeutic landscape and future outlook are examined, with particular attention to the potential therapeutic roles of IL-6 inhibitors and JAK inhibitors, alongside an elucidation of prevailing limitations and avenues for further research. This study contributes essential theoretical groundwork and clinical insights for both diagnosing and managing VEXAS syndrome.