DynG: a dynamic scaling factor for thermographic stomatal conductance estimation under changing environmental conditions.

Thermal imaging is a key plant phenotyping and monitoring technique but faces major bottlenecks in accurately and efficiently inferring stomatal conductance (g) from leaf temperature. The conductance index (I) was previously proposed to estimate g from thermography by linking temperature differences between real and artificial leaves (ALs) based on the leaf energy balance. However, I is highly sensitive to environmental fluctuations, hampering interpretation and reducing reproducibility.

Activated Dendritic Cell Membrane-Engineered Nanoformulation of Metallo-Immunomodulators as Lysosome-Targeted Adjuvants for Synergistic Cancer Immunotherapy.

Combination of chemotherapy and cancer immunotherapy has shown substantial clinical promise. However, the immunosuppressive tumor microenvironment (TME) poses a critical barrier to this combination therapy. Here, a tumor lysosome-targeted immunomodulatory strategy based on a biomimetic nanoadjuvant is presented, which effectively overcomes the immunosuppressive TME and demonstrates enhanced therapeutic efficacy when combined with chemotherapy.

Pancancer outcome prediction via a unified weakly supervised deep learning model.

Accurate prognosis prediction is essential for guiding cancer treatment and improving patient outcomes. While recent studies have demonstrated the potential of histopathological images in survival analysis, existing models are typically developed in a cancer-specific manner, lack extensive external validation, and often rely on molecular data that are not routinely available in clinical practice. To address these limitations, we present PROGPATH, a unified model capable of integrating histopathological image features with routinely collected clinical variables to achieve pancancer prognosis prediction.

Association between cardiometabolic index and sarcopenia: 2011-2018 National Health and Nutrition Examination survey (NHANES).

Background: The cardiometabolic index (CMI) is a reliable marker used to assess the degree of obesity and lipid metabolism disorders in individuals. Emerging evidence indicates that disorders of lipid metabolism and sarcopenia share a common pathophysiologic basis. However, few studies have investigated the association between CMI and sarcopenia.

Ioning out glioblastoma: ferroptosis mechanisms and therapeutic frontiers.

Glioblastoma (GBM) (IDH-wildtype), the most prevalent and malignant primary brain tumor in adults, continues to pose a major therapeutic challenge in neuro-oncology. Despite significant advancements in cancer diagnosis and treatment technologies, conventional therapies remain largely ineffective against this tumor, urgently necessitating breakthrough treatment strategies. This comprehensive review critically examines recent advances in targeting ferroptosis, an iron-dependent form of non-apoptotic cell death mediated through reactive oxygen species (ROS) accumulation and lipid membrane peroxidation, for therapeutic intervention in GBM.

Machine-Learning-Driven Stochastic Modeling Method for 3D Asphalt Mixture Reconstruction from 2D Images.

Three-dimensional reconstruction programs are essential tools for understanding the behavior of asphalt mixtures. On the basis of accurate 3D models, it is convenient to identify the complex relationship between spatial structures and physical properties. In this work, we explore a low-cost and data-efficient way to create a collection of 3D asphalt mixture models.

Real-Time Three-Dimensional Imaging of Cell-Substrate Adhesion Structures Based on Plasmonic Scattering Microscopy.

Real-time monitoring of cell-substrate interactions remains a significant challenge in cellular biomechanics. Here, a plasmonic scattering microscopy (PSM) integrated with three-dimensional image reconstruction is presented for real-time analysis of the cell-substrate interface, simultaneously achieving submicrometer spatial resolution. The system was validated by imaging microspheres with known geometries and achieved a mean coefficient of determination of 86% in the reconstructed images.

Investigating the mechanical behavior of anti-impact airbag fabrics: a structural design approach.

. This study introduces a cutting-edge approach to enhance safety protection through the innovative structural design of anti-impact cushion airbag fabrics, with significant implications for the clothing industry and sports safety. .

Risk and protective factors for bereavement adaptation: a protocol for a systematic review and meta-analysis.

Introduction: Many people experience lifelong impacts after losing a loved one. Bereavement adaptation, which refers to how people adapt to changes after a death, is crucial for their subsequent life stages. Bereavement experienced during one's childhood or teenage years can be even more challenging, considering the dual burden of bereavement adaptation and developmental tasks.

Vitreous Olink Proteomics Uncovers Novel Inflammatory Proteins in Patients with Proliferative Diabetic Retinopathy.

Mounting research indicates that an inflammatory environment is a key driver in the advancement of proliferative diabetic retinopathy (PDR). In this study, we analyze and contrast 92 inflammatory cytokine levels in the vitreous humor of individuals with PDR ( = 14) with those of control subjects diagnosed with idiopathic macular hole (IMH; = 11), by using the Olink inflammation panel. Key findings revealed 22 differentially expressed proteins (DEPs) when comparing the PDR and IMH groups, with 21 proteins showing increased expression and only one demonstrating decreased levels.

Megawatt peak power, repetition rate tunable, high beam quality nanosecond QCW-LD end-pumped Nd:YVO MOPA system.

A megawatt (MW) peak power, tunable repetition rate nanosecond (ns) laser system based on a quasi-continuous wave (QCW) laser diode (LD) end-pumped master oscillator power amplifier (MOPA) structure was demonstrated. A 1064 nm electro-optically Q-switched Nd:YVO laser was used as the seed source, generating a pulse duration of 4.6 ns, a single pulse energy of 530 μJ, a repetition rate of 1 kHz, and beam quality factors of  = 1.

Large energy, narrow bandwidth 1550 nm picosecond polarization-maintaining fiber laser.

A large energy, narrow bandwidth picosecond polarization-maintaining fiber laser operating at 1550 nm has been demonstrated. The seed laser is a self-starting Er-doped fiber oscillator based on a Figure-9 configuration, generating pulses with a duration of 48 ps and a repetition rate of 15 MHz. To reduce spectral broadening during subsequent amplification, the pulse spectrum is reshaped into a near-Gaussian profile using a narrowband uniform fiber Bragg grating (FBG).

34.3 W, 172 µJ, 1342 nm picosecond master oscillator power amplifier.

A high-power, high-energy 1342 nm picosecond Nd:YVO master oscillator power amplifier (MOPA) laser system was demonstrated, comprising a SESAM mode-locked oscillator, a regenerative amplifier, and four main amplification stages consisting of two double-pass amplifiers and two single-pass amplifiers. Low-doping Nd:YVO crystals with undoped end caps, combined with 880 nm laser diode in-band pumping technique, were used to mitigate thermal effects. A pulse energy as high as 710 µJ at 10 kHz was obtained from the regenerative amplifier.

3D-printed SPME-based wooden-tip mass spectrometry for rapid detection of organic ultraviolet absorbers in complex matrices.

Organic ultraviolet absorbers (OUVs), commonly used in sunscreens and industrial products, have raised growing environmental and health concerns due to their pervasive occurrence in aquatic ecosystems. Conventional analytical techniques, such as liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS), offer high sensitivity but are constrained by labor-intensive workflows and extensive solvent use. Here, we present a rapid and portable screening method for seven priority OUVs by integrating a C-modified wooden-tip solid-phase microextraction (SPME) probe with ambient mass spectrometry (AMS).

Comparative efficacy and safety of acupuncture for adolescent depression: protocol for a systematic review and Bayesian network meta-analysis.

Background: Adolescents are in a critical stage of development and represent a high-risk population for depression. Various studies have demonstrated the efficacy of acupuncture therapies in the treatment of adolescent depression. However, trials directly comparing the efficacy and safety of different acupuncture therapies for adolescent depression are still lacking.

A metal-drug self-delivery nanomedicine alleviates tumor immunosuppression to potentiate synergistic chemo/chemodynamic therapy against hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the most common primary liver cancer with a poor prognosis. Chemotherapy is one of the first-line clinical therapeutic strategies for HCC. Still, the effectiveness of chemotherapy is hampered by the tumor immunosuppressive microenvironment and drug resistance caused by insufficient delivery.

Comparative evaluation of positive and negative LC-MS modes for DOM profiling.

Dissolved organic matter (DOM) in marine environments is critical for nutrient cycling and carbon storage, forming a fundamental part of the ocean's biogeochemical cycles. Traditionally, DOM analysis has utilized negative electrospray ionization (ESI-) mass spectrometry, yet positive electrospray ionization (ESI+) mode has recently gained traction. However, few studies have compared ESI+ and ESI- to understand how these modes impact the overall DOM profiling results.

Intensive Value Utilization of Food-Derived Marine Immunoactive Peptides: Optimizing the Process Yield and Improving the Delivery Efficiency According to the Immune Activity Mechanism and Assisted Enzymatic Hydrolysis.

Food-borne marine active peptides have been increasingly used as functional products for postoperative rehabilitation. However, there are still many problems, such as low protein yield and absorption rate. Therefore, the assisted enzymatic hydrolysis process and activity of marine immunoreactive peptides have been the focus of widespread attention.

Home-Based Exercise for Improving Balance Ability in Post-Stroke Patients: A Systematic Review and Meta-Analysis.

Background: Home-based exercise offers a cost-effective way to receive thorough rehabilitation without the requirement of costly supervised treatment.

Aim: To investigate the effects of home-based exercise on the balance ability in post-stroke patients.

Methods: A thorough search was carried out on various databases, such as Cochrane Library, Web of Science, PubMed, Embase, and China National Knowledge Infrastructure Library, until October 2024.

A Mendelian randomization study of the gut microbiota and risk of knee osteoarthritis and the mediating role of immune cells.

With increasing research on the gut microbiota (GM), there is growing evidence suggesting that GM may influence the risk of knee osteoarthritis (KOA) by modulating immune cell activity. However, the causal relationship between GM, immune cells, and KOA has not been thoroughly investigated. This study aimed to investigate the causal effect of GM on KOA and to identify immune cell mechanisms that may play a mediating role.

Noninvasive and Precise Transdermal Drug Delivery Using Spatiotemporally Responsive Lipid Vesicles in Conjunction with Ultrasound.

Transdermal drug delivery (TDD) is influenced by the multiple anatomical layers of skin and various barriers, making the precise delivery of multiple drugs to specific spatial locations for optimal therapeutic efficacy a challenging prospect. This study proposes a strategy involving the use of spatiotemporally responsive lipid vesicles in conjunction with ultrasound (360 kHz, 1 W) for achieving noninvasive and precise TDD. The lipid vesicles prepared using microfluidic technology exhibited differences in particle size, loading capacity, and ultrasound responsiveness.

Plant-Derived Bioactive Peptides: Extraction, Isolation, Purification, Pharmacological Activities, Structure-Activity Relationship, and Applications.

Plant-derived bioactive peptides (PDBPs) have become a key research focus owing to their multiple targets and high safety. However, current challenges in this field primarily include the low efficiency of traditional extraction techniques, the complex structure-activity relationships of PDBPs, the scalability of novel technologies, inadequate understanding of multisystem synergistic effects, and the scarcity of human clinical trials. To address these gaps, future research should integrate artificial intelligence to establish an integrated technological system spanning computer-aided design, targeted preparation, and activity verification, while prioritizing efforts to elucidate the mechanisms of multisystem synergism, develop environmentally friendly extraction processes and targeted delivery systems, and facilitate the translation of PDBPs from basic research to functional products.

BBSNet: An Intelligent Grading Method for Pork Freshness Based on Few-Shot Learning.

Deep learning approaches for pork freshness grading typically require large datasets, which limits their practical application due to the high costs associated with data collection. To address this challenge, we propose BBSNet, a lightweight few-shot learning model designed for accurate freshness classification with a limited number of images. BBSNet incorporates a batch channel normalization (BCN) layer to enhance feature distinguishability and employs BiFormer for optimized fine-grained feature extraction.

PXseg: automatic tooth segmentation, numbering and abnormal morphology detection based on CBCT and panoramic radiographs.

Objective: PXseg, a novel approach for tooth segmentation, numbering and abnormal morphology detection in panoramic X-ray (PX), was designed and promoted through optimizing annotation and applying pre-training.

Methods: Derived from multicenter, ctPXs generated from cone beam computed tomography (CBCT) with accurate 3D labels were utilized for pre-training, while conventional PXs (cPXs) with 2D labels were input for training. Visual and statistical analyses were conducted using the internal dataset to assess segmentation and numbering performances of PXseg and compared with the model without ctPX pre-training, while the accuracy of PXseg detecting abnormal teeth was evaluated using the external dataset consisting of cPXs with complex dental diseases.