Biomechanical analysis of the tandem spinal external fixation in a multiple-level noncontiguous lumbar fractures model: a finite element analysis.

Objective: This study aimed to investigate the biomechanical characteristics of the tandem spinal external fixation (TSEF) for treating multilevel noncontiguous spinal fracture (MNSF) using finite element analysis and provide a theoretical basis for clinical application. Methods: We constructed two models of L2 and L4 vertebral fractures that were fixed with the TSEF and the long-segment spinal inner fixation (LSIF). The range of motion (ROM), maximum stresses at L2 and L4 vertebrae, the screws and rods, and the intervertebral discs of the two models were recorded under load control. Subsequently, the required torque, the maximum stress at L2 and L4 vertebrae, the screws and rods, and the intervertebral discs were analyzed under displacement control. Results: Under load control, the TSEF model reserved more ROM than the LSIF model. The maximum stresses of screws in the TSEF model were increased, while the maximum stresses of rods were reduced compared to the LSIF model. Moreover, the maximum stresses of L2 and L4 vertebrae and discs in the TSEF model were increased compared to the LSIF model. Under displacement control, the TSEF model required fewer moments (N·mm) than the LSIF model. Compared to the LSIF model, the maximum stresses of screws and rods in the TSEF model have decreased; the maximum stresses at L2 and L4 in the TSEF model were increased. In the flexion condition, the maximum stresses of discs in the TSEF model were less than the LSIF model, while the maximum stresses of discs in the TSEF model were higher in the extension condition. Conclusion: Compared to LSIF, the TSEF has a better stress distribution with higher overall mobility. Theoretically, it reduces the stress concentration of the connecting rods and the stress shielding of the fractured vertebral bodies.

AttABseq: an attention-based deep learning prediction method for antigen-antibody binding affinity changes based on protein sequences.

The optimization of therapeutic antibodies through traditional techniques, such as candidate screening via hybridoma or phage display, is resource-intensive and time-consuming. In recent years, computational and artificial intelligence-based methods have been actively developed to accelerate and improve the development of therapeutic antibodies. In this study, we developed an end-to-end sequence-based deep learning model, termed AttABseq, for the predictions of the antigen-antibody binding affinity changes connected with antibody mutations. AttABseq is a highly efficient and generic attention-based model by utilizing diverse antigen-antibody complex sequences as the input to predict the binding affinity changes of residue mutations. The assessment on the three benchmark datasets illustrates that AttABseq is 120% more accurate than other sequence-based models in terms of the Pearson correlation coefficient between the predicted and experimental binding affinity changes. Moreover, AttABseq also either outperforms or competes favorably with the structure-based approaches. Furthermore, AttABseq consistently demonstrates robust predictive capabilities across a diverse array of conditions, underscoring its remarkable capacity for generalization across a wide spectrum of antigen-antibody complexes. It imposes no constraints on the quantity of altered residues, rendering it particularly applicable in scenarios where crystallographic structures remain unavailable. The attention-based interpretability analysis indicates that the causal effects of point mutations on antibody-antigen binding affinity changes can be visualized at the residue level, which might assist automated antibody sequence optimization. We believe that AttABseq provides a fiercely competitive answer to therapeutic antibody optimization.

Symptomatic Heart Failure and Clonal Hematopoiesis-related Mutations in Patients with Acute Myeloid Leukemia.

Clonal hematopoiesis of indeterminate potential (CHIP) is a common risk factor for both hematological malignancies and cardiovascular (CV) diseases. The purpose of this study was to investigate the association between CHIP-related mutations and symptomatic heart failure in patients diagnosed with acute myeloid leukemia (AML). A total of 563 patients with newly-diagnosed AML who underwent DNA sequencing of bone marrow before treatment were retrospectively investigated. Cox proportional hazard regression models and Fine and Gray's subdistribution hazard regression models were used to assess the association between CHIP-related mutations and symptomatic heart failure (HF). 79.0% patients had at least 1 CHIP-related mutation; the most frequent mutations were DNMT3A, ASXL1 and TET2. Fifty-one patients (9.1%) developed symptomatic HF. The incidence of symptomatic HF was more frequent in patients with DNMT3A mutations (P<0.01), with a 1-year cumulative incidence of symptomatic HF in patients with DNMT3A mutations of 11.4%, compared to 3.9% in wild-type DNMT3A patients (P<0.01). After adjustment for age and anthracyclines dose, DNMT3A mutations remained independently correlated with HF (HR: 2.32, 95% CI: 1.26-4.29, P=0.01). In conclusion, in patients with AML, the presence of DNMT3A mutations was associated with a 2-fold increased risk for symptomatic HF irrespective of age and anthracyclines use.

Complement-Coagulation Cross-talk: Factor H-mediated regulation of the Complement Classical Pathway activation by fibrin clots.

The classical pathway of the complement system is activated by the binding of C1q in the C1 complex to the target activator, including immune complexes. Factor H is regarded as the key downregulatory protein of the complement alternative pathway. However, both C1q and factor H bind to target surfaces via charge distribution patterns. For a few targets, C1q and factor H compete for binding to common or overlapping sites. Factor H, therefore, can effectively regulate the classical pathway activation through such targets, in addition to its previously characterized role in the alternative pathway. Both C1q and factor H are known to recognize foreign or altered-self materials, e.g., bacteria, viruses, and apoptotic/necrotic cells. Clots, formed by the coagulation system, are an example of altered self. Factor H is present abundantly in platelets and is a well-known substrate for FXIIIa. Here, we investigated whether clots activate the complement classical pathway and whether this is regulated by factor H. We show here that both C1q and factor H bind to the fibrin formed in microtiter plates and the fibrin clots formed under in vitro physiological conditions. Both C1q and factor H become covalently bound to fibrin clots, and this is mediated via FXIIIa. We also show that fibrin clots activate the classical pathway of complement, as demonstrated by C4 consumption and membrane attack complex detection assays. Thus, factor H downregulates the activation of the classical pathway induced by fibrin clots. These results elucidate the intricate molecular mechanisms through which the complement and coagulation pathways intersect and have regulatory consequences.

TransfIGN: A Structure-Based Deep Learning Method for Modeling the Interaction between HLA-A*02:01 and Antigen Peptides.

The intricate interaction between major histocompatibility complexes (MHCs) and antigen peptides with diverse amino acid sequences plays a pivotal role in immune responses and T cell activity. In recent years, deep learning (DL)-based models have emerged as promising tools for accelerating antigen peptide screening. However, most of these models solely rely on one-dimensional amino acid sequences, overlooking crucial information required for the three-dimensional (3-D) space binding process. In this study, we propose TransfIGN, a structure-based DL model that is inspired by our previously developed framework, Interaction Graph Network (IGN), and incorporates sequence information from transformers to predict the interactions between HLA-A*02:01 and antigen peptides. Our model, trained on a comprehensive data set containing 61,816 sequences with 9051 binding affinity labels and 56,848 eluted ligand labels, achieves an area under the curve (AUC) of 0.893 on the binary data set, better than state-of-the-art sequence-based models trained on larger data sets such as NetMHCpan4.1, ANN, and TransPHLA. Furthermore, when evaluated on the IEDB weekly benchmark data sets, our predictions (AUC = 0.816) are better than those of the recommended methods like the IEDB consensus (AUC = 0.795). Notably, the interaction weight matrices generated by our method highlight the strong interactions at specific positions within peptides, emphasizing the model's ability to provide physical interpretability. This capability to unveil binding mechanisms through intricate structural features holds promise for new immunotherapeutic avenues.

Characterizing ammonia emission from light-duty gasoline vehicles under the influence of multiple factors and its correlation with conventional pollutants.

Ammonia (NH3), which is a precursor of secondary particulate matter (PM), can be produced through three-way catalyst (TWC) side reactions in light-duty gasoline vehicles (LDGVs), posing a threat to human health and air quality. To explore ammonia emission characteristics, 8 LDGVs and 1 hybrid electric light-duty vehicle (HEV) with various mileages traveled were analyzed with a chassis dynamometer system during regulation driving cycles. The emission factors of the adopted China VI in-use LDGVs were 7.04 ± 2.61 mg/km under cold-start conditions and 4.94 ± 1.69 mg/km under hot-start conditions. With increasing mileage traveled, the total ammonia emissions increased, and the difference between the cold/hot-start results decreased. The emissions of in-use LDGVs with bi-fuel engines were analyzed, and more ammonia was generated in the compressed natural gas (CNG) mode through the hydrocarbon (HC) reforming reaction. The relationship between the emissions of ammonia and conventional pollutants was established. During the initial cold-start phase, a delay in ammonia formation was observed, and the ammonia emissions conformed with the CO and HC emissions after exhaust heating. Vehicle specific power (VSP) analysis revealed that the interval of highest ammonia emissions corresponded to acceleration events at high speeds. For the HEV, the transition from motor to engine drive conditions contributed to ammonia emission occurrence because of the more pronounced cold-start events. The use of HEV technology could introduce additional uncertainties in controlling urban ammonia emissions. Detailed analysis of emission characteristics could provide data support for future research on ammonia emission standards and control strategies for LDGVs.

Capsaicin pretreatment attenuates salt-sensitive hypertension by alleviating AMPK/Akt/Nrf2 pathway in hypothalamic paraventricular nucleus.

Background: Long term hypertension seriously promotes target organ damage in the brain and heart, and has increasingly become serious public health problem worldwide. The anti-hypertensive effects of capsaicin has been reported, however, the role and mechanism of capsaicin within the brain on salt-induced hypertension have yet to be elucidated. This study aimed to verify the hypothesis that capsaicin attenuates salt-induced hypertension via the AMPK/Akt/Nrf2 pathway in hypothalamic paraventricular nucleus (PVN). Methods: Dahl salt-sensitive (Dahl S) rats were used as animal model for the present study. Rats were randomly divided into four groups based on their dietary regimen (0.3% normal salt diet and 8% high salt diet) and treatment methods (infusion of vehicle or capsaicin in the PVN). Capsaicin was chronically administered in the PVN throughout the animal experiment phase of the study that lasted 6 weeks. Results: Our results demonstrated that PVN pretreatment with capsaicin can slow down raise of the blood pressure elevation and heart rate (HR) of Dahl S hypertensive rats given high salt diet. Interestingly, the cardiac hypertrophy was significantly improved. Furthermore, PVN pretreatment with capsaicin induced decrease in the expression of mRNA expression of NADPH oxidase-2 (NOX2), inducible nitric oxide synthase (iNOS), NOX4, p-IKKß and proinflammatory cytokines and increase in number of positive cell level for Nrf2 and HO-1 in the PVN of Dahl S hypertensive rats. Additionally, the protein expressions of phosphatidylinositol 3-kinase (p-PI3K) and phosphorylated protein kinase-B (p-AKT) were decreased, phosphorylated adenosine monophosphate-activated protein kinase (p-AMPK) were increased after the PVN pretreatment with capsaicin. Conclusion: Capsaicin pretreatment attenuates salt-sensitive hypertension by alleviating AMPK/Akt/iNOS pathway in the PVN.

Non-fibril amyloid aggregation at the air/water interface: self-adaptive pathway resulting in a 2D Janus nanofilm.

The amyloid states of proteins are implicated in several neurodegenerative diseases and bioadhesion processes. However, the classical amyloid fibrillization mechanism fails to adequately explain the formation of polymorphic aggregates and their adhesion to various surfaces. Herein, we report a non-fibril amyloid aggregation pathway, with disulfide-bond-reduced lysozyme (R-Lyz) as a model protein under quasi-physiological conditions. Very different from classical fibrillization, this pathway begins with the air-water interface (AWI) accelerated oligomerization of unfolded full-length protein, resulting in unique plate-like oligomers with self-adaptive ability, which can adjust their conformations to match various interfaces such as the asymmetric AWI and amyloid-protein film surface. The pathway enables a stepwise packing of the plate-like oligomers into a 2D Janus nanofilm, exhibiting a divergent distribution of hydrophilic/hydrophobic residues on opposite sides of the nanofilm. The resulting Janus nanofilm possesses a top-level Young's modulus (8.3 ± 0.6 GPa) among amyloid-based materials and exhibits adhesive strength two times higher (145 ± 81 kPa) than that of barnacle cement. Furthermore, we found that such an interface-directed pathway exists in several amyloidogenic proteins with a similar self-adaptive 2D-aggregation process, including bovine serum albumin, insulin, fibrinogen, hemoglobin, lactoferrin, and ovalbumin. Thus, our findings on the non-fibril self-adaptive mechanism for amyloid aggregation may shed light on polymorphic amyloid assembly and their adhesions through an alternative pathway.

The potential of integrating stereotactic ablative radiotherapy techniques with hyperfractionation for lung cancer.

BACKGROUND: Limited literature exists on the feasibility and effectiveness of integrating stereotactic ablative radiotherapy (SABR) techniques with hyperfractionated regimens for patients with lung cancer. This study aims to assess whether the SABR technique with hyperfractionation can potentially reduce lung toxicity. METHODS: We utilized the linear-quadratic model to find the optimal fraction to maximize the tumor biological equivalent dose (BED) to normal-tissue BED ratio. Validation was performed by comparing the SABR plans with 50 Gy/5 fractions and hyperfractionationed plans with 88.8 Gy/74 fractions with the same tumor BED and planning criteria for 10 patients with early-stage lung cancer. Mean lung BED, Lyman-Kutcher-Burman (LKB) normal tissue complication probability (NTCP), critical volume (CV) criteria (volume below BED of 22.92 and 25.65 Gy, and mean BED for lowest 1000 and 1500 cc) and the percentage of the lung receiving 20Gy or more (V20) were compared using the Wilcoxon signed-rank test. RESULTS: The transition point occurs when the tumor-to-normal tissue ratio (TNR) of the physical dose equals the TNR of α/ß in the BED dose-volume histogram of the lung. Compared with the hypofractionated regimen, the hyperfractionated regimen is superior in the dose range above but inferior below the transition point. The hyperfractionated regimen showed a lower mean lung BED (6.40 Gy vs. 7.73 Gy) and NTCP (3.50% vs. 4.21%), with inferior results concerning CV criteria and higher V20 (7.37% vs. 7.03%) in comparison with the hypofractionated regimen (p < 0.01 for all). CONCLUSIONS: The hyperfractionated regimen has an advantage in the high-dose region of the lung but a disadvantage in the low-dose region. Further research is needed to determine the superiority between hypo- and hyperfractionation.

Biohybrid Nanorobots Carrying Glycoengineered Extracellular Vesicles Promote Diabetic Wound Repair through Dual-Enhanced Cell and Tissue Penetration.

Considerable progress has been made in the development of drug delivery systems for diabetic wounds. However, underlying drawbacks, such as low delivery efficiency and poor tissue permeability, have rarely been addressed. In this study, a multifunctional biohybrid nanorobot platform comprising an artificial unit and several biological components is constructed. The artificial unit is a magnetically driven nanorobot surface modified with antibacterial 2-hydroxypropyltrimethyl ammonium chloride chitosan, which enables the entire platform to move and has excellent tissue penetration capacity. The biological components are two-step engineered extracellular vesicles that are first loaded with mangiferin, a natural polyphenolic compound with antioxidant properties, and then glycoengineered on the surface to enhance cellular uptake efficiency. As expected, the platform is more easily absorbed by endothelial cells and fibroblasts and exhibits outstanding dermal penetration performance and antioxidant properties. Encouraging results are also observed in infected diabetic wound models, showing improved wound re-epithelialization, collagen deposition, angiogenesis, and accelerated wound healing. Collectively, a biohybrid nanorobot platform that possesses the functionalities of both artificial units and biological components serves as an efficient delivery system to promote diabetic wound repair through dual-enhanced cell and tissue penetration and multistep interventions.

DrugFlow: An AI-Driven One-Stop Platform for Innovative Drug Discovery.

Artificial intelligence (AI)-aided drug design has demonstrated unprecedented effects on modern drug discovery, but there is still an urgent need for user-friendly interfaces that bridge the gap between these sophisticated tools and scientists, particularly those who are less computer savvy. Herein, we present DrugFlow, an AI-driven one-stop platform that offers a clean, convenient, and cloud-based interface to streamline early drug discovery workflows. By seamlessly integrating a range of innovative AI algorithms, covering molecular docking, quantitative structure-activity relationship modeling, molecular generation, ADMET (absorption, distribution, metabolism, excretion and toxicity) prediction, and virtual screening, DrugFlow can offer effective AI solutions for almost all crucial stages in early drug discovery, including hit identification and hit/lead optimization. We hope that the platform can provide sufficiently valuable guidance to aid real-word drug design and discovery. The platform is available at https://drugflow.com.

Effects of Exclusive Breastfeeding Duration on Pneumonia Occurrence and Course in Infants Up to 6 Months of Age: A Case-Control Study.

We aimed to analyze the effects of exclusive breastfeeding duration on the occurrence and course of pneumonia in infants aged up to 6 months. Prospective case-control study. This study was conducted from August 2020 to August 2022 at a maternity and child health hospital in China. A total of 218 infants up to 6 months of age with pneumonia were included in the analyses. Health data were obtained using a hospitalization information system or an interview-based questionnaire. Univariate and multivariate logistic regression analyses were performed to analyze the data. The incidence of pneumonia, hospitalization duration, and costs to participants were significantly affected by the duration of exclusive breastfeeding (p < 0.01). The incidence of pneumonia among participants with different exclusive breastfeeding durations also differed significantly (p < 0.01). The shorter the duration of exclusive breastfeeding, the higher the incidence of pneumonia among infants. We found that the longer the exclusive breastfeeding duration in infants up to 6 months of age, the lower the recurrence of pneumonia, the shorter the hospital stay, and the lower the hospital costs. The rate of exclusive breastfeeding for infants up to 6 months of age should be increased as much as possible to reduce the occurrence of pneumonia and hospital costs.

Alpha-tocopherol inhibits ferroptosis and promotes neural function recovery in rats with spinal cord injury via downregulating Alox15.

Spinal cord injury (SCI) is a type of central nervous system (CNS) injury in which ferroptosis is becoming a promising target for treatment. Alpha-tocopherol (Vitamin E, Vit E) is a compound with anti-ferroptosis activity. The mechanism of alpha-tocopherol in regulating ferroptosis after SCI has not been deeply studied. In this study, rats with SCI were treated by Alpha-tocopherol based on bioinformatic analysis and molecular docking prediction. Behavioral tests and histological findings showed that Alpha-tocopherol promoted neural function recovery and tissue repairment in rats with SCI. Subsequently, regulatory effects of Alpha-tocopherol on Alox15 and ferroptosis were detected and then localized by immunofluorescence. In vitro, alpha-tocopherol improved the ROS accumulation, iron overload, lipid peroxidation and mitochondrial dysfunction. The effects of Alpha-tocopherol on the expression of Alox15, Ptgs2 and 4Hne were validated in vitro. Finally, the inhibitory effects of Alpha-tocopherol on Alox15 and ferroptosis were weakened by the mutation of 87th residue of Alox15. In summary, alpha-tocopherol could alleviate SCI-induced ferroptosis by downregulating Alox15 to promote neural function recovery in rats with SCI. Findings in this study could help further our understanding on SCI-induced ferroptosis and provide a novel insight for treating SCI.

Amine-Terminated Phenanthroline Diimides as Aqueous Masking Agents for Am(III)/Eu(III) Separation: An Alternative Ligand Design Strategy for Water-Soluble Lanthanide/Actinide Chelating Ligands.

Selective actinide coordination (from lanthanides) is critical for both nuclear waste management and sustainable development of nuclear power. Hydrophilic ligands used as masking agents to withhold actinides in the aqueous phase are currently highly pursued, while synthetic accessibility, water solubility, acid resistance, and extraction capability are the remaining problems. Most reported hydrophilic ligands are only effective at low acidity. We recently proved that the phenanthroline diimide skeleton was an efficient building block for the construction of highly efficient acid-resistant hydrophilic lanthanide/actinide separation agents, while the limited water solubility hindered the loading capability of the ligand. Herein, amine was introduced as the terminal solubilizing group onto the phenanthroline diimide backbone, which after protonation in acid showed high water solubility. The positively charged terminal amines enhanced the ligand water solubility to a large extent, which, on the other side, was believed to be detrimental for the coordination and complexation of the metal cations. We showed that by delicately adjusting the alkyl chain spacing, this intuitive disadvantage could be relieved and superior extraction performances could be achieved. This work holds significance for both hydrophilic lanthanide/actinide separation ligand design and, concurrently, offers insights into the development of water-soluble lanthanide/actinide complexes for biomedical and bioimaging applications.

Structural characterization and prebiotic activity of rhamnogalacturonan-I rich pumpkin pectic polysaccharide extracted by alkaline solution.

The present study aimed to investigate the structural and physicochemical characteristics of alkali-extracted pectic polysaccharide (AkPP) and to evaluate its prebiotic effects. AkPP was obtained from pumpkin pulp using an alkaline extraction method. AkPP, which had a molecular weight (Mw) of mainly 13.67 kDa and an esterification degree of 9.60%, was composed mainly of galacturonic acid (GalA), rhamnose (Rha), galactose, and arabinose. The ratio of the homogalacturonan (HG) region to the rhamnogalacturonan-I (RG-I) region in AkPP was 48.74:43.62. In the nuclear magnetic resonance spectrum, the signals indicating α-1,4-linked D-GalA, α-1,2-linked L-Rha, α-1,2,4-linked L-Rha residues were well resolved, demonstrating the presence of the HG and RG-I regions in its molecular structure. Collectively, AkPP was low methoxyl pectin rich in the RG-I region with short side chains and had a low Mw. Thermal analysis revealed that AkPP had good thermal stability. Compared to inulin, AkPP more effectively promoted the proliferation of Lactobacillus acidophilus, Lacticaseibacillus rhamnosus GG, Lacticaseibacillus casei, and Lacticaseibacillus paracasei and the production of lactic, acetic, and propionic acids. This study presents the unique structural features of AkPP and provides a scientific basis for further investigation of the potential of AkPP as a promising prebiotic.

Improving the Prognostic Evaluation Precision of Hospital Outcomes for Heart Failure Using Admission Notes and Clinical Tabular Data: Multimodal Deep Learning Model.

BACKGROUND: Clinical notes contain contextualized information beyond structured data related to patients' past and current health status. OBJECTIVE: This study aimed to design a multimodal deep learning approach to improve the evaluation precision of hospital outcomes for heart failure (HF) using admission clinical notes and easily collected tabular data. METHODS: Data for the development and validation of the multimodal model were retrospectively derived from 3 open-access US databases, including the Medical Information Mart for Intensive Care III v1.4 (MIMIC-III) and MIMIC-IV v1.0, collected from a teaching hospital from 2001 to 2019, and the eICU Collaborative Research Database v1.2, collected from 208 hospitals from 2014 to 2015. The study cohorts consisted of all patients with critical HF. The clinical notes, including chief complaint, history of present illness, physical examination, medical history, and admission medication, as well as clinical variables recorded in electronic health records, were analyzed. We developed a deep learning mortality prediction model for in-hospital patients, which underwent complete internal, prospective, and external evaluation. The Integrated Gradients and SHapley Additive exPlanations (SHAP) methods were used to analyze the importance of risk factors. RESULTS: The study included 9989 (16.4%) patients in the development set, 2497 (14.1%) patients in the internal validation set, 1896 (18.3%) in the prospective validation set, and 7432 (15%) patients in the external validation set. The area under the receiver operating characteristic curve of the models was 0.838 (95% CI 0.827-0.851), 0.849 (95% CI 0.841-0.856), and 0.767 (95% CI 0.762-0.772), for the internal, prospective, and external validation sets, respectively. The area under the receiver operating characteristic curve of the multimodal model outperformed that of the unimodal models in all test sets, and tabular data contributed to higher discrimination. The medical history and physical examination were more useful than other factors in early assessments. CONCLUSIONS: The multimodal deep learning model for combining admission notes and clinical tabular data showed promising efficacy as a potentially novel method in evaluating the risk of mortality in patients with HF, providing more accurate and timely decision support.

Clinical characteristics and status of treatment of small-cell carcinoma of the ovary, hypercalcemic type in the Chinese population: a meta-analysis.

OBJECTIVE: This study aimed to comprehensively analyze the clinical characteristics and treatment status of Chinese small cell carcinoma of the ovary hypercalcemic type (SCCOHT) patients, providing insights into this unique population and comparing findings with international literature. METHODS: Through a meta-analysis, we collected data from published case reports and records from the Obstetrics & Gynecology Hospital of Fudan University. Demographic information, clinical presentations, tumor attributes, treatment modalities, and survival outcomes were extracted and examined alongside relevant global studies. RESULTS: The analysis encompassed 80 Chinese SCCOHT patients, of which 62 from 33 previously reported literatures, and the other 18 were from Obstetrics & Gynecology Hospital of Fudan University. In 62 cases with stage information, A total of 25 tumors were International Federation of Gynecology and Obstetrics stage I, 3 were stage II, 19 were stage III, and 15 were stage IV. Most patients received surgery and chemotherapy, but regimens were varied. Median follow-up was 10 months (range=4-120). Elevated carbohydrate antigen 125 and serum calcium levels were consistent findings. Recurrence rates were notable, especially among stage I patients. Platinum-based chemotherapy, paclitaxel and carboplatin (n=11, 13.4%), constituted common treatment regimens. CONCLUSION: This study observed demographic and clinical similarities with international datasets. And the findings emphasize the urgency for innovative therapeutic approaches to improve outcomes in SCCOHT patients. Continued research efforts are essential to enhance the knowledge surrounding this rare malignancy and to optimize its clinical management.

A Plasmonic Optoelectronic Resistive Random-Access Memory for In-Sensor Color Image Cryptography.

The optoelectronic resistive random-access memory (RRAM) with the integrated function of perception, storage and intrinsic randomness displays promising applications in the hardware level in-sensor image cryptography. In this work, 2D hexagonal boron nitride based optoelectronic RRAM is fabricated with semitransparent noble metal (Ag or Au) as top electrodes, which can simultaneous capture color image and generate physically unclonable function (PUF) key for in-sensor color image cryptography. Surface plasmons of noble metals enable the strong light absorption to realize an efficient modulation of filament growth at nanoscale. Resistive switching curves show that the optical stimuli can impede the filament aggregation and promote the filament annihilation, which originates from photothermal effects and photogenerated hot electrons in localized surface plasmon resonance of noble metals. By selecting noble metals, the optoelectronic RRAM array can respond to distinct wavelengths and mimic the biological dichromatic cone cells to perform the color perception. Due to the intrinsic and high-quality randomness, the optoelectronic RRAM can produce a PUF key in every exposure cycle, which can be applied in the reconfigurable cryptography. The findings demonstrate an effective strategy to build optoelectronic RRAM for in-sensor color image cryptography applications.

Genome-wide characterization of LEA gene family reveals a positive role of BnaA.LEA6.a in freezing tolerance in rapeseed (Brassica napus L.).

BACKGROUND: Freezing stress is one of the major abiotic stresses that causes extensive damage to plants. LEA (Late embryogenesis abundant) proteins play a crucial role in plant growth, development, and abiotic stress. However, there is limited research on the function of LEA genes in low-temperature stress in Brassica napus (rapeseed). RESULTS: Total 306 potential LEA genes were identified in B. rapa (79), B. oleracea (79) and B. napus (148) and divided into eight subgroups. LEA genes of the same subgroup had similar gene structures and predicted subcellular locations. Cis-regulatory elements analysis showed that the promoters of BnaLEA genes rich in cis-regulatory elements related to various abiotic stresses. Additionally, RNA-seq and real-time PCR results indicated that the majority of BnaLEA family members were highly expressed in senescent tissues of rapeseed, especially during late stages of seed maturation, and most BnaLEA genes can be induced by salt and osmotic stress. Interestingly, the BnaA.LEA6.a and BnaC.LEA6.a genes were highly expressed across different vegetative and reproductive organs during different development stages, and showed strong responses to salt, osmotic, and cold stress, particularly freezing stress. Further analysis showed that overexpression of BnaA.LEA6.a increased the freezing tolerance in rapeseed, as evidenced by lower relative electrical leakage and higher survival rates compared to the wild-type (WT) under freezing treatment. CONCLUSION: This study is of great significance for understanding the functions of BnaLEA genes in freezing tolerance in rapeseed and offers an ideal candidate gene (BnaA.LEA6.a) for molecular breeding of freezing-tolerant rapeseed cultivars.