Early cancer screening surveillance in one medical center of China.

Objectives: Cancer screening aims to detect and treat malignant lesions at an early stage and to prolong patients' lifetime. There is still a lack of effective cancer screening programs in China. We initiated a screening project in 2018 and this study presented the cancer screening status in China. Methods: We conducted a cross-sectional study in one cancer-care medical center of China. The screening program included routine blood tests, plasma tumor markers, gastric endoscopy, colonoscopy, ultrasound, and computed tomography (CT) scans. Screening results were presented as sensitivity, specificity and positive predictive values (PPVs). Results: Twenty-three (1.46%) out of 1,576 participants were eventually diagnosed with malignant tumors or high-grade intraepithelial neoplasia (HGIN). A family history of malignancy (78.26% in diagnosed cancer and HGIN vs. 46.36% in the others) was the only statistically significant parameter associated with cancer detection (p = 0.002). None of the common tumor markers were associated with the cancers screened. Except for colonoscopy (50.00%) and ultrasound for renal cancer (66.67%), the sensitivities of most screening methods were 100%. The specificities of all the screening means were above 96%. Most PPVs ranged from 30-60%. Conclusion: We emphasized risk stratification for early cancer screening, such as a family history of cancer. The survey illustrated that gastric endoscopy, colonoscopy, ultrasound, and lung CT for early cancer screening had high specificity, reasonable sensitivity, and PPV. We anticipated this report would motivate larger-sample studies to estimate the risk-to-benefit ratio of cancer screening and urge the establishment of a native Chinese screening project and even guidelines.

The U -shape relationship between free fatty acid level and adverse outcomes in coronary artery disease patients with hypertension: evidence from a large prospective cohort study.

BACKGROUND: Evidence is scarce on the effect of free fatty acid (FFA) level in the prognosis of coronary artery disease (CAD) patients with hypertension. This study. METHODS: A large prospective cohort study with a follow-up period of average 2 years was conducted at Xinjiang Medical University Affiliated First Hospital from December 2016 to October 2021. A total of 10,395 CAD participants were divided into groups based on FFA concentration and hypertension status, and then primary outcome mortality and secondary endpoint ischemic events were assessed in the different groups. RESULTS: A total of 222 all-cause mortality (ACMs), 164 cardiac mortality (CMs), 718 major adverse cardiovascular events (MACEs) and 803 major adverse cardiovascular and cerebrovascular events (MACCEs) were recorded during follow-up period. A nonlinear relationship between FFA and adverse outcomes was observed only in CAD patients with hypertension. Namely, a "U -shape" relationship between FFA levels and long-term outcomes was found in CAD patients with hypertension. Lower FFA level (< 310 µmol/L), or higher FFA level (≥ 580 µmol/L) at baseline is independent risk factors for adverse outcomes. After adjustment for confounders, excess FFA increases mortality (ACM, HR = 1.957, 95%CI(1.240-3.087), P = 0.004; CM, HR = 2.704, 95%CI(1.495-4.890, P = 0.001) and MACE (HR = 1.411, 95%CI(1.077-1.848), P = 0.012), MACCE (HR = 1.299, 95%CI (1.013-1.666), P = 0.040) prevalence. Low levels of FFA at baseline can also increase the incidence of MACE (HR = 1.567,95%CI (1.187-2.069), P = 0.002) and MACCE (HR = 1.387, 95%CI (1.070-1.798), P = 0.013). CONCLUSIONS: Baseline FFA concentrations significantly associated with long-term mortality and ischemic events could be a better and novel risk biomarker for prognosis prediction in CAD patients with hypertension. TRIAL REGISTRATION: The details of the design were registered on https://www.chictr.org.cn/ (Identifier NCT05174143).

Detection of foodborne methicillin-resistant Staphylococcus aureus via fluorescence-encoded microsphere and Argonaute-mediated decoding.

Molecular diagnosis of foodborne methicillin-resistant Staphylococcus aureus (MRSA) is crucial for controlling its dissemination and ensuring food safety. However, existing genetic methods are limited by susceptibility to aerosol contamination and restricted to single-gene detection. Herein, a fluorescent biosensor employing fluorescence-encoded microspheres and Argonaute-mediated decoding is developed, enabling ultrasensitive, accurate, and duplex detection of MRSA genes. This assay utilizes a target-triggered polymerization/nicking reaction to cyclically produce specific guide DNA, guiding Argonaute protein to site-specifically cleave the molecular beacon on the microsphere, thereby decoding a fluorescent signal. Notably, the fluorescence-encoded microsphere, designed via on-tetrahedron rolling circle amplification, achieves high fluorescence loadings in a unit area. This biosensor demonstrates simultaneous detection of two unamplified MRSA genes, mecA and femA, at concentrations as low as 0.63 fM and 0.48 fM, respectively. Moreover, the method exhibited excellent recoveries in milk, egg, and pork samples ranging from 73% to 112%, highlighting its practicability in real scenarios.

A dual-gene panel of two fragments of methylated IRF4 and one of ZEB2 in plasma cell-free DNA for gastric cancer detection.

Early detection is crucial for increasing the survival rate of gastric cancer (GC). We aimed to identify a methylated cell-free DNA (cfDNA) marker panel for detecting GC. The differentially methylated CpGs (DMCs) were selected from datasets of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The selected DMCs were validated and further selected in tissue samples (40 gastric cancer and 36 healthy white blood cell samples) and in a quarter sample volume of plasma samples (37 gastric cancer, 12 benign gastric disease, and 43 healthy individuals). The marker combination selected was then evaluated in a normal sample volume of plasma samples (35 gastric cancer, 39 control diseases, and 40 healthy individuals) using real-time methylation-specific PCR (MSP). The analysis of the results compared methods based on 2-ΔΔCt values and Ct values. In the results, 30 DMCs were selected through bioinformatics methods, and then 5 were selected for biological validation. The marker combination of two fragments of IRF4 (IRF4-1 and IRF4-2) and one of ZEB2 was selected due to its good performance. The Ct-based method was selected for its good results and practical advantages. The assay, IRF4-1 and IRF4-2 in one fluorescence channel and ZEB2 in another, obtained 74.3% sensitivity for the GC group at any stage, at 92.4% specificity. In conclusion, the panel of IRF4 and ZEB2 in plasma cfDNA demonstrates good diagnostic performance and application potential in clinical settings.

Unlocking Potential of Pyrochlore in Energy Systems via Soft Voting Ensemble Learning.

In traditional machine learning (ML)-based material design, the defects of low prediction accuracy, overfitting and low generalization ability are mainly caused by the training of a single ML model. Here, a Soft Voting Ensemble Learning (SVEL) approach is proposed to solve the above issues by integrating multiple ML models in the same scene, thus pursuing more stable and reliable prediction. As a case study, SVEL is applied to develop the broad chemical space of novel pyrochlore electrocatalysts with the molecular formula of A2B2O7, to explore promising pyrochlore oxides and accelerate predictions of unknown pyrochlore in the periodic table. The model successfully established the structure-property relationship of pyrochlore, and selected six cost-effective pyrochlore from the periodic table with a high prediction accuracy of 91.7%, all of which showed good electrocatalytic performance. SVEL not only effectively avoids the high costs of experimentation and lengthy computations, but also addresses biases arising from data scarcity in single models. Furthermore, it has significantly reduced the research cycle of pyrochlore by ≈ 22 years, offering broad prospects for accelerating the development of materials genomics. SVEL method is intended to integrate multiple AI models to provide broader model training clues for the AI material design community.

Ethanolic extract from Sophora moorcroftiana inhibit cell proliferation and alter the mechanical properties of human cervical cancer.

BACKGROUND: Cervical cancer is one of the most common gynecological malignancies. Previous studies have shown that the ethanol extract of Sophora moorcroftiana seeds (EESMS) possesses an antiproliferative effect on several tumors in vitro. Therefore, in this study, we assessed the impact of EESMS on human cervical carcinoma (HeLa) cell proliferation. METHODS: The proliferation and apoptotic effects of HeLa cells treated with EESMS were evaluated using 3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide assay, dual acridine orange/ethidium bromide double staining, flow cytometry, and western blotting. Single-cell level atomic force microscopy (AFM) was conducted to detect the mechanical properties of HeLa cells, and proteomics and bioinformatics methods were used to elucidate the molecular mechanisms of EESMS. RESULTS: EESMS treatment inhibited HeLa cell proliferation by blocking the G0/G1 phase, increasing the expression of Caspase-3 and affecting its mechanical properties, and the EESMS indicated no significant inhibitory effect on mouse fibroblasts L929 cell line. In total, 218 differentially expressed proteins were identified using two-dimensional electrophoresis, and eight differentially expressed proteins were successfully identified using matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry. The differentially expressed proteins were involved in various cellular and biological processes. CONCLUSION: This study provides a perspective on how cells change through biomechanics and a further theoretical foundation for the future application of Sophora moorcroftiana as a novel low-toxicity chemotherapy medication for treating human cervical cancer.

Advanced Gastric Cancer: CT Radiomics Prediction of Lymph Modes Metastasis After Neoadjuvant Chemotherapy.

This study aims to create and assess machine learning models for predicting lymph node metastases following neoadjuvant treatment in advanced gastric cancer (AGC) using baseline and restaging computed tomography (CT). We evaluated CT images and pathological data from 158 patients with resected stomach cancer from two institutions in this retrospective analysis. Patients were eligible for inclusion if they had histologically proven gastric cancer. They had received neoadjuvant chemotherapy, with at least 15 lymph nodes removed. All patients received baseline and preoperative abdominal CT and had complete clinicopathological reports. They were divided into two cohorts: (a) the primary cohort (n = 125) for model creation and (b) the testing cohort (n = 33) for evaluating models' capacity to predict the existence of lymph node metastases. The diagnostic ability of the radiomics-model for lymph node metastasis was compared to traditional CT morphological diagnosis by radiologist. The radiomics model based on the baseline and preoperative CT images produced encouraging results in the training group (AUC 0.846) and testing cohort (AUC 0.843). In the training cohort, the sensitivity and specificity were 81.3% and 77.8%, respectively, whereas in the testing cohort, they were 84% and 75%. The diagnostic sensitivity and specificity of the radiologist were 70% and 42.2% (using baseline CT) and 46.3% and 62.2% (using preoperative CT). In particular, the specificity of radiomics model was higher than that of conventional CT in diagnosing N0 cases (no lymph node metastasis). The CT-based radiomics model could assess lymph node metastasis more accurately than traditional CT imaging in AGC patients following neoadjuvant chemotherapy.

Anode-Free Aqueous Aluminum Ion Batteries.

Aqueous aluminum ion batteries (AAIBs) possess the advantages of high safety, cost-effectiveness, eco-friendliness and high theoretical capacity. However, the Al2O3 film on the Al anode surface, a natural physical barrier to the plating of hydrated aluminum ions, is a key factor in the decomposition of the aqueous electrolyte and the severe hydrogen precipitation reaction. To circumvent the obnoxious Al anode, a proof-of-concept of an anode-free AAIB is first proposed, in which Al2TiO5, as a cathode pre-aluminum additive (Al source), can replenish Al loss by over cycling. The Al-Cu alloy layer, formed by plating Al on the Cu foil surface during the charge process, possesses a reversible electrochemical property and is paired with a polyaniline (cathode) to stimulate the battery to exhibit high initial discharge capacity (175 mAh g-1), high power density (≈410 Wh L-1) and ultra-long cycle life (4000 cycles) with the capacity retention of ≈60% after 1000 cycles. This work will act as a primer to ignite the enormous prospective researches on the anode-free aqueous Al ion batteries.

4D-Printed MXene-Based Artificial Nerve Guidance Conduit for Enhanced Regeneration of Peripheral Nerve Injuries.

Repairing larger defects (>5 mm) in peripheral nerve injuries (PNIs) remains a significant challenge when using traditional artificial nerve guidance conduits (NGCs). A novel approach that combines 4D printing technology with poly(L-lactide-co-trimethylene carbonate) (PLATMC) and Ti3C2Tx MXene nanosheets is proposed, thereby imparting shape memory properties to the NGCs. Upon body temperature activation, the printed sheet-like structure can quickly self-roll into a conduit-like structure, enabling optimal wrapping around nerve stumps. This design enhances nerve fixation and simplifies surgical procedures. Moreover, the integration of microchannel expertly crafted through 4D printing, along with the incorporation of MXene nanosheets, introduces electrical conductivity. This feature facilitates the guided and directional migration of nerve cells, rapidly accelerating the healing of the PNI. By leveraging these advanced technologies, the developed NGCs demonstrate remarkable potential in promoting peripheral nerve regeneration, leading to substantial improvements in muscle morphology and restored sciatic nerve function, comparable to outcomes achieved through autogenous nerve transplantation.

High-Entropy Alloy Electrocatalysts Bidirectionally Promote Lithium Polysulfide Conversions for Long-Cycle-Life Lithium-Sulfur Batteries.

High-entropy alloys (HEAs) have attracted considerable attention, owing to their exceptional characteristics and high configurational entropy. Recent findings demonstrated that incorporating HEAs into sulfur cathodes can alleviate the shuttling effect of lithium polysulfides (LiPSs) and accelerate their redox reactions. Herein, we synthesized nano Pt0.25Cu0.25Fe0.15Co0.15Ni0.2 HEAs on hollow carbons (HCs; denoted as HEA/HC) by a facile pyrolysis strategy. The HEA/HC nanostructures were further integrated into hypha carbon nanobelts (HCNBs). The solid-solution phase formed by the uniform mixture of the five metal elements, i.e., Pt0.25Cu0.25Fe0.15Co0.15Ni0.2 HEAs, gave rise to a strong interaction between neighboring atoms in different metals, resulting in their adsorption energy transformation across a wide, multipeak, and nearly continuous spectrum. Meanwhile, the HEAs exhibited numerous active sites on their surface, which is beneficial to catalyzing the cascade conversion of LiPSs. Combining density functional theory (DFT) calculations with detailed experimental investigations, the prepared HEAs bidirectionally catalyze the cascade reactions of LiPSs and boost their conversion reaction rates. S/HEA@HC/HCNB cathodes achieved a low 0.034% decay rate for 2000 cycles at 1.0 C. Notably, the S/HEA@HC/HCNB cathode delivered a high initial areal capacity of 10.2 mAh cm-2 with a sulfur loading of 9 mg cm-2 at 0.1 C. The assembled pouch cell exhibited a capacity of 1077.9 mAh g-1 at the first discharge at 0.1 C. The capacity declined to 71.3% after 43 cycles at 0.1 C. In this work, we propose to utilize HEAs as catalysts not only to improve the cycling stability of lithium-sulfur batteries, but also to promote HEAs in energy storage applications.

Sea Cucumber-Inspired Microneedle Nerve Guidance Conduit for Synergistically Inhibiting Muscle Atrophy and Promoting Nerve Regeneration.

Muscle atrophy resulting from peripheral nerve injury (PNI) poses a threat to a patient's mobility and sensitivity. However, an effective method to inhibit muscle atrophy following PNI remains elusive. Drawing inspiration from the sea cucumber, we have integrated microneedles (MNs) and microchannel technology into nerve guidance conduits (NGCs) to develop bionic microneedle NGCs (MNGCs) that emulate the structure and piezoelectric function of sea cucumbers. Morphologically, MNGCs feature an outer surface with outward-pointing needle tips capable of applying electrical stimulation to denervated muscles. Simultaneously, the interior contains microchannels designed to guide the migration of Schwann cells (SCs). Physiologically, the incorporation of conductive reduced graphene oxide and piezoelectric zinc oxide nanoparticles into the polycaprolactone scaffold enhances conductivity and piezoelectric properties, facilitating SCs' migration, myelin regeneration, axon growth, and the restoration of neuromuscular function. These combined effects ultimately lead to the inhibition of muscle atrophy and the restoration of nerve function. Consequently, the concept of the synergistic effect of inhibiting muscle atrophy and promoting nerve regeneration has the capacity to transform the traditional approach to PNI repair and find broad applications in PNI repair.

Safety and clinical efficacy of microwave ablation combined with percutaneous vertebroplasty in the treatment of multisegmental spinal metastases.

OBJECTIVE: To evaluate the safety and efficacy of microwave ablation (MWA) combined with percutaneous vertebroplasty (PVP) in the treatment of multisegmental (2-3 segments) osteolytic spinal metastases. MATERIALS AND METHODS: This study comprised a retrospective analysis of data from 20 patients with multisegmental (2-3 segments) osteolytic spinal metastases who received MWA combined with PVP. The visual analog scale (VAS) score, Oswestry Disability Index (ODI) score, Quality of Life Questionnaire-Bone Metastases 22 (QLQ-BM22), and local recurrence before and after the operation were measured. The occurrence of complications was observed to evaluate safety. RESULTS: All operations were completed successfully with no serious complications. Transient nerve injury occurred in two cases, but recovered after symptomatic treatment. The bone cement leakage rate was 13.9% (6/43). The mean baseline VAS scores were 7.25 ± 0.91 before treatment and 7.25 ± 0.91, 3.70 ± 1.12, 2.70 ± 0.73, 2.40 ± 0.68, 2.25 ± 0.71, and 2.70 ± 0.92 at 1 day, 1 week, 1, 3, and 6 months after treatment; all values were significantly lower (P < 0.001). The mean baseline ODI score decreased from 56.90 ± 9.74 before treatment to 41.90 ± 7.09, 38.10 ± 7.93, and 38.80 ± 10.59 at 1, 3, and 6 months after treatment, respectively; all values were significantly lower (P < 0.001). The average QLQ-BM22 baseline score decreased from 54.10 ± 5.36 before treatment to 44.65 ± 5.22, 43.05 ± 4.78, 42.30 ± 4.06, and 42.15 ± 5.47 at 1 week, 1, 3, and 6 months after treatment; all values were significantly lower (all P < 0.001). The postoperative survival time of all patients was >6 months. In three patients, four vertebral segments recurred 6 months after operation. CONCLUSION: MWA combined with PVP is a safe and effective treatment for multisegmental osteolytic vertebral metastases that can effectively relieve pain, improve spinal function, improve quality of life, and delay tumor progression. However, it is a long operation, necessitating good preoperative preparation and effective intraoperative pain relief measures.

3D printing nacre powder/sodium alginate scaffold loaded with PRF promotes bone tissue repair and regeneration.

Bone defects are a common complication of bone diseases, which often affect the quality of life and mental health of patients. The use of biomimetic bone scaffolds loaded with bioactive substances has become a focal point in the research on bone defect repair. In this study, composite scaffolds resembling bone tissue were created using nacre powder (NP) and sodium alginate (SA) through 3D printing. These scaffolds exhibit several physiological structural and mechanical characteristics of bone tissue, such as suitable porosity, an appropriate pore size, applicable degradation performance and satisfying the mechanical requirements of cancellous bone, etc. Then, platelet-rich fibrin (PRF), containing a mass of growth factors, was loaded on the NP/SA scaffolds. This was aimed to fully maximize the synergistic effect with NP, thereby accelerating bone tissue regeneration. Overall, this study marks the first instance of preparing a bionic bone structure scaffold containing NP by 3D printing technology, which is combined with PRF to further accelerate bone regeneration. These findings offer a new treatment strategy for bone tissue regeneration in clinical applications.

Mitochondrial Localized In Situ Self-Assembly Reprogramming Tumor Immune and Metabolic Microenvironment for Enhanced Cancer Therapy.

The inherent immune and metabolic tumor microenvironment (TME) of most solid tumors adversely affect the antitumor efficacy of various treatments, which is an urgent issue to be solved in clinical cancer therapy. In this study, a mitochondrial localized in situ self-assembly system is constructed to remodel the TME by improving immunogenicity and disrupting the metabolic plasticity of cancer cells. The peptide-based drug delivery system can be pre-assembled into nanomicelles in vitro and form functional nanofibers on mitochondria through a cascade-responsive process involving reductive release, targeted enrichment, and in situ self-assembly. The organelle-specific in situ self-assemblyeffectively switches the role of mitophagy from pro-survival to pro-death, which finally induces intense endoplasmic reticulum stress and atypical type II immunogenic cell death. Disintegration of the mitochondrial ultrastructure also impedes the metabolic plasticity of tumor cells, which greatly promotes the immunosuppresive TME remodeling into an immunostimulatory TME. Ultimately, the mitochondrial localized in situ self-assembly system effectively suppresses tumor metastases, and converts cold tumors into hot tumors with enhanced sensitivity to radiotherapy and immune checkpoint blockade therapy. This study offers a universal strategy for spatiotemporally controlling supramolecular self-assembly on sub-organelles to determine cancer cell fate and enhance cancer therapy.

Clinical efficacy and safety of microwave ablation combined with percutaneous osteoplasty for palliative treatment in pelvic osteolytic metastases.

OBJECTIVES: To evaluate the impact of microwave ablation (MWA) on pain relief, quality of life, mobility, and local tumour progression in adult patients with pelvic osteolytic bone metastasis and to test the safety of MWA. METHODS: This study retrospectively analysed the data from 20 patients with pelvic osteolytic metastases who received MWA combined with percutaneous osteoplasty (POP). The visual analogue scale (VAS), musculoskeletal tumour society system (MSTS), and Quality of Life Questionnaire-Bone Metastases 22 (QLQ-BM22) were used to evaluate the pain, limb function, and quality of life. The intraoperative and postoperative complications were recorded. The tumour recurrence and survival time were analysed during the follow-up period (range 3-26 months). RESULTS: All (n = 20) MWA and POP operations were completed successfully. Four patients (20%; 95% CI, 6%-44%) had mild bone cement leakage from surrounding tissues, and there were no obvious symptoms or serious complications. There were significant differences in VAS, MSTS, and QLQ-BM22 scores before and after the operation (P < .001). During the postoperative follow-up period, 9 patients died. The median survival time was 8 months (range 3-26 months; IQR: 4.5-13; 95% CI, 4.2-15.3 months), and the 1-year survival rate was 65% (13/20; 95% CI, 41%-85%). Tumour recurrence occurred in 4 cases (20%; 95% CI, 6%-44%) after the operation, and the median time of recurrence was 12 months (range 8-16 months; IQR: 8.25-12.75; 95% CI, 5.5-18.5 months). CONCLUSIONS: MWA combined with POP is an effective and safe treatment for pelvic osteolytic metastases. It can significantly relieve local pain, reconstruct limb function, improve patients' quality of life, and effectively control local tumour progression. ADVANCES IN KNOWLEDGE: So far, the experience of using microwave in the treatment of pelvic metastases is still limited. MWA combined with POP in the treatment of pelvic osteolytic metastases can provide significant clinical benefits in acceptable low-risk minimally invasive situations and should be provided to patients with appropriate pelvic metastases in a multidisciplinary approach.

RotNet: A Rotationally Invariant Graph Neural Network for Quantum Mechanical Calculations.

Deep learning has proven promising in biological and chemical applications, aiding in accurate predictions of properties such as atomic forces, energies, and material band gaps. Traditional methods with rotational invariance, one of the most crucial physical laws for predictions made by machine learning, have relied on Fourier transforms or specialized convolution filters, leading to complex model design and reduced accuracy and efficiency. However, models without rotational invariance exhibit poor generalization ability across datasets. Addressing this contradiction, this work proposes a rotationally invariant graph neural network, named RotNet, for accurate and accelerated quantum mechanical calculations that can overcome the generalization deficiency caused by rotations of molecules. RotNet ensures rotational invariance through an effective transformation and learns distance and angular information from atomic coordinates. Benchmark experiments on three datasets (protein fragments, electronic materials, and QM9) demonstrate that the proposed RotNet framework outperforms popular baselines and generalizes well to spatial data with varying rotations. The high accuracy, efficiency, and fast convergence of RotNet suggest that it has tremendous potential to significantly facilitate studies of protein dynamics simulation and materials engineering while maintaining physical plausibility.

CEEM: a Chemically Explainable Deep Learning Platform for Identifying Compounds with Low Effective Mass.

The semiconductor industry occupies a crucial position in the fields of integrated circuits, energy, and communication systems. Effective mass (mE ), which is closely related to electron transition, thermal excitation, and carrier mobility, is a key performance indicator of semiconductor. However, the highly neglected mE is onerous to measure experimentally, which seriously hinders the evaluation of semiconductor properties and the understanding of the carrier migration mechanisms. Here, a chemically explainable effective mass predictive platform (CEEM) is constructed by deep learning, to identify n-type and p-type semiconductors with low mE . Based on the graph network, a versatile explainable network is innovatively designed that enables CEEM to efficiently predict the mE of any structure, with the area under the curve of 0.904 for n-type semiconductors and 0.896 for p-type semiconductors, and derive the most relevant chemical factors. Using CEEM, the currently largest mE database is built that contains 126 335 entries and screens out 466 semiconductors with low mE for transparent conductive materials, photovoltaic materials, and water-splitting materials. Moreover, a user-friendly and interactive CEEM web is provided that supports query, prediction, and explanation of mE . CEEM's high efficiency, accuracy, flexibility, and explainability open up new avenues for the discovery and design of high-performance semiconductors.

The Tautomerase Activity of Tumor Exosomal MIF Promotes Pancreatic Cancer Progression by Modulating MDSC Differentiation.

Pancreatic cancer is a deadly disease that is largely resistant to immunotherapy, in part because of the accumulation of immunosuppressive cells in the tumor microenvironment (TME). Much evidence suggests that tumor-derived exosomes (TDE) contribute to the immunosuppressive activity mediated by myeloid-derived suppressor cells (MDSC) within the pancreatic cancer TME. However, the underlying mechanisms remain elusive. Herein, we report that macrophage migration inhibitory factor (MIF) in TDEs has a key role in inducing MDSC formation in pancreatic cancer. We identified MIF in both human and murine pancreatic cancer-derived exosomes. Upon specific shRNA-mediated knockdown of MIF, the ability of pancreatic cancer-derived exosomes to promote MDSC differentiation was abrogated. This phenotype was rescued by reexpression of the wild-type form of MIF rather than a tautomerase-null mutant or a thiol-protein oxidoreductase-null mutant, indicating that both MIF enzyme activity sites play a role in exosome-induced MDSC formation in pancreatic cancer. RNA sequencing data indicated that MIF tautomerase regulated the expression of genes required for MDSC differentiation, recruitment, and activation. We therefore developed a MIF tautomerase inhibitor, IPG1576. The inhibitor effectively inhibited exosome-induced MDSC differentiation in vitro and reduced tumor growth in an orthotopic pancreatic cancer model, which was associated with decreased numbers of MDSCs and increased infiltration of CD8+ T cells in the TME. Collectively, our findings highlight a pivotal role for MIF in exosome-induced MDSC differentiation in pancreatic cancer and underscore the potential of MIF tautomerase inhibitors to reverse the immunosuppressive pancreatic cancer microenvironment, thereby augmenting anticancer immune responses.

MatGPT: A Vane of Materials Informatics from Past, Present, to Future.

Combining materials science, artificial intelligence (AI), physical chemistry, and other disciplines, materials informatics is continuously accelerating the vigorous development of new materials. The emergence of "GPT (Generative Pre-trained Transformer) AI" shows that the scientific research field has entered the era of intelligent civilization with "data" as the basic factor and "algorithm + computing power" as the core productivity. The continuous innovation of AI will impact the cognitive laws and scientific methods, and reconstruct the knowledge and wisdom system. This leads to think more about materials informatics. Here, a comprehensive discussion of AI models and materials infrastructures is provided, and the advances in the discovery and design of new materials are reviewed. With the rise of new research paradigms triggered by "AI for Science", the vane of materials informatics: "MatGPT", is proposed and the technical path planning from the aspects of data, descriptors, generative models, pretraining models, directed design models, collaborative training, experimental robots, as well as the efforts and preparations needed to develop a new generation of materials informatics, is carried out. Finally, the challenges and constraints faced by materials informatics are discussed, in order to achieve a more digital, intelligent, and automated construction of materials informatics with the joint efforts of more interdisciplinary scientists.

Surfactants Influencing the Biocatalytic Performance of Natural Alkane-Degrading Bacteria via Interfacial Biocatalysis in Pickering Emulsions.

Setting superhydrophobic Mycobacterium sp. as an example, the hydrophobic bacteria acting as demulsifying agents of surfactant-stabilized conventional emulsions, vice versa, the synergistic/antagonistic influence of nonionic surfactants (Tween 80 or Span 80) on the stability of the bacteria-stabilized Pickering emulsions was investigated. At the same time, the activated/suppression effect of nonionic surfactants on microbial degradation of tetradecane, which exhibited a dose-response relationship, was also found. The hydrophobic bacteria acting as demulsifying agents and the suppression influence of nonionic surfactants on the biocatalytic performance (indexing as biomass) of natural alkane-degrading bacteria, believed to be totally separated concepts previously, are for the first time found to be closely related to in situ surface modification of bacteria with nonionic surfactants. During the degradation of tetradecane by Mycobacterium sp. in the presence of nonionic surfactants, demulsification due to the bacteria acting as demulsifying agents and interfacial biocatalysis in the bacteria-stabilized Pickering emulsions are involved, which provides useful information to select optimal dispersants for marine oil spills.