Diabetes mellitus, characterized by glucose metabolism disorders and marked by insulin deficiency or insulin resistance, has seen a continuous rise in prevalence. In recent years, islet transplantation has matured as a therapeutic approach for diabetes, becoming an important method for glycemic control and the reduction of diabetes-related complications. Donor selection directly influences transplant outcomes, and various research institutions worldwide have proposed multiple scoring systems to optimize donor assessment, such as the University of Alberta scoring system and the North American Islet Donor Score. This article explores the impact of key factors such as donor age, body mass index and ischemia time on islet transplantation. Combining practical experience in pancreatic donor selection from Shanghai Changzheng Hospital, it proposes screening criteria for pancreatic donors suitable for China, aiming to provide new evidence for improving the success rate of islet transplantation.

OBJECTIVE To investigate the ameliorative effect and potential mechanism of imperatorin （IMP） on doxorubicin （DOX） resistance in breast cancer. METHODS The effects of maximum non-toxic concentration （100 μg/mL） of IMP combined with different concentrations of DOX （12.5， 25， 50， 75， 100 μg/mL） on the proliferation of MCF-7/DOX cells were determined by MTT method. MCF-7/DOX cells were divided into blank control group （1‰ dimethyl sulfoxide）， DOX group （50 μg/mL）， IMP+DOX group （100 μg/mL IMP+50 μg/mL DOX） and IMP group （100 μg/mL）. mRNA and protein expressions of multidrug resistance protein 1 （MDR1） and multidrug resistance-associated protein 1 in each group were measured. The relevant pathways and targets involved in the improvement of DOX resistance in breast cancer cells by IMP were screened and validated by using transcriptome sequencing technology， along with gene ontology （GO） enrichment analyses and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analyses. RESULTS Compared with DOX alone， the combination of IMP and DOX reduced the half inhibitory concentration of DOX on MCF-7/DOX cells from 81.965 μg/mL to 43.170 μg/mL， the reverse fold was 1.90， and the mRNA expression of MDR1 was significantly down-regulated （P＜0.05）. The results of GO enrichment analyses and KEGG pathway enrichment analyses indicated that the reversal of DOX resistance in breast cancer by IMP was mainly associated with the regulation of biological processes such as detoxification， multiple biological processes， and cell killing. The main pathway involved was the p53 signaling pathway， and the key targets mainly included constitutively photomorphogenic protein 1 （COP1）， cyclin E1 （CCNE1）， growth arrest and DNA damage-inducible protein 45A E-mail：tangxilan1983@163.com （GADD45A） and GADD45B. The results of the verification experiments showed that compared with DOX group， there was a trend of up-regulation of COP1 mRNA， and significant down- regulation of CCNE1， GADD45A， and GADD45B mRNA expression in IMP+DOX group （P＜0.05）. CONCLUSIONS The effect of IMP in ameliorating DOX resistance in breast cancer is related to its regulation of COP1， CCNE1， GADD45A and GADD45B targets in the p53 signaling pathway.

OBJECTIVE To evaluate the efficacy and safety of high-dose ilaprazole combined with amoxicillin for newly diagnosed elderly patients with Helicobacter pylori （Hp） infection， and analyze independent risk factors for failure of Hp infection eradication treatment. METHODS Totally 200 cases of newly diagnosed elderly patients with Hp infection in Xinxiang Central Hospital from August 1， 2021 to December 1， 2024 were selected and randomly divided into control group and study group， with 100 cases in each group. The control group was treated with classic quadruple therapy regimen （Amoxicillin capsules+ Clarithromycin tablets+Bismuth potassium citrate tablets+Ilaprazole enteric-coated tablets）. The study group was treated with high- dose Ilaprazole enteric-coated tablets+Amoxicillin capsules. All patients were administered medication for 2 weeks. Hp eradication rates in the two groups were compared using intention-to-treat （ITT） and per-protocol （PP） analyses. The incidence of adverse reactions in both groups was also recorded. The multiple-factor Logistic regression analysis was used to identify independent risk factors for failure of Hp infection eradication treatment. RESULTS In ITT and PP analyses， there was no significant difference of Hp eradication rates between the two groups （P＞0.05）. There was no significant difference in incidence of mild to moderate adverse reactions between the two groups （P＞0.05）. BMI ≤18.5 kg/m2， BMI ＞23.9 kg/m2， rural residence， concomitant diabetes and concomitant heart disease were identified as independent risk factors influencing the failure of Hp infection eradication treatment （P＜0.05）. CONCLUSIONS The efficacy and safety of high-dose ilaprazole combined with amoxicillin are comparable to classic quadruple therapy regimen in treating newly diagnosed elderly patients with Hp infection. Independent risk factors influencing the failure of Hp infection eradication treatment include BMI ≤18.5 kg/m2， BMI ＞23.9 kg/m2， rural residence， concomitant diabetes and concomitant heart disease.

Medical institutions, with their clinical practice foundation and abundant human use experience data, have become important carriers for the inheritance and innovation of traditional Chinese medicine(TCM) and the "cradles" of the preparation of new TCM. To effectively promote the transformation of new TCM originating from the TCM clinical practice in medical institutions and establish an effective evaluation index system for the transformation of new TCM conforming to the characteristics of TCM, consensus experts adopted the literature research, questionnaire survey, Delphi method, etc. By focusing on the policy and technical evaluation of new TCM originating from the TCM clinical practice in medical institutions, a comprehensive evaluation from the dimensions of drug safety, efficacy, feasibility, and characteristic advantages was conducted, thus forming a comprehensive evaluation system with four primary indicators and 37 secondary indicators. The expert consensus reached aims to encourage medical institutions at all levels to continuously improve the high-quality research and development and transformation of new TCM originating from the TCM clinical practice in medical institutions and targeted at clinical needs, so as to provide a decision-making basis for the preparation, selection, cultivation, and transformation of new TCM for medical institutions, improve the development efficiency of new TCM, and precisely respond to the public medication needs.
Medicine, Chinese Traditional/standards* ; Humans ; Consensus ; Drugs, Chinese Herbal/therapeutic use* ; Surveys and Questionnaires

Based on latent structure model and association rule analysis, this study investigates the prescription patterns used by professor YANG Zhong-qi in treating hypertension with traditional Chinese medicine(TCM) and infers the associated TCM syndromes, providing a reference for clinical syndrome differentiation and treatment. The observation window spanned from January 8, 2013, to June 26, 2024, during which qualified herbal decoction prescriptions meeting efficacy criteria were extracted from the outpatient medical record system of the First Affiliated Hospital of Guangzhou University of Chinese Medicine and compiled into a standardized database. Statistical analysis of high-frequency herbs included frequency counts and herbal property-channel tropism analysis. Latent structure modeling and association rule analysis were performed using R 4.3.2 and Lantern 5.0 software to identify core herbal combinations and infer TCM syndrome patterns. A total of 2 436 TCM prescriptions were included in the study, involving 263 drugs with a cumulative frequency of 29 783. High-frequency herbs comprised Uncariae Ramulus cum Uncis, Poria, Glycyrrhizae Radix et Rhizoma, Puerariae Lobatae Radix, and Alismatis Rhizoma, predominantly categorized as deficiency-tonifying, heat-clearing, and blood-activating and stasis-resolving herbs. Latent structure analysis identified 18 latent variables, 74 latent classes, 5 comprehensive clustering models, and 15 core herbal combinations, suggesting that the core syndrome clusters include liver Yang hyperactivity pattern, Yin deficiency with Yang hyperactivity pattern, phlegm-stasis intermingling pattern, and liver-kidney insufficiency pattern. Association rule analysis revealed 22 robust association rules. RESULTS:: indicate that hypertension manifests as a deficiency-rooted excess manifestation, significantly associated with functional dysregulation of the liver, lung, spleen-stomach, heart, and kidney. Key pathogenic mechanisms involve liver Yang hyperactivity, phlegm-stasis interaction, and liver-kidney insufficiency. Therapeutic strategies should prioritize liver-calming, spleen-fortifying, and deficiency-tonifying principles, supplemented by dynamic regulation of Qi-blood and Yin-Yang balance according to syndrome evolution, alongside pathogen-eliminating methods such as phlegm-resolving and stasis-dispelling. Synergistic interventions like mind-tranquilizing therapies should be tailored to individual conditions.
Hypertension/drug therapy* ; Drugs, Chinese Herbal/therapeutic use* ; Humans ; Medicine, Chinese Traditional ; Drug Prescriptions ; Latent Class Analysis

In the clinical stage, suspected hemolytic plasma may cause hemolysis illness, manifesting as symptoms such as heart failure, severe anemia, etc. Applying a deep learning method to plasma images significantly improves recognition accuracy, so that this paper proposes a plasma quality detection model based on improved "You Only Look Once" 5th version (YOLOv5). Then the model presented in this paper and the evaluation system ‌were introduced‌ into the plasma datasets, and ‌the average accuracy of the final classification reached 98.7%‌. The results of this paper's experiment were obtained through the combination of several key algorithm modules including‌ omni-dimensional dynamic convolution, pooling with separable kernel attention, residual bi-fusion feature pyramid network, ‌and‌ re-parameterization convolution. The method of this paper‌ obtains the feature information of spatial mapping efficiently, and enhances the average recognition accuracy of plasma quality detection. This paper presents a high-efficiency detection method for plasma images, aiming to provide a practical approach to prevent hemolysis illnesses caused by external factors.
Algorithms ; Humans ; Hemolysis ; Plasma ; Deep Learning ; Image Processing, Computer-Assisted/methods*

Diabetic cardiomyopathy (DCM) is a medical condition characterized by cardiac remodeling and dysfunction in individuals with diabetes mellitus. Sarcoplasmic reticulum (SR) and mitochondrial Ca²⁺ overload in cardiomyocytes have been recognized as biological hallmarks in DCM; however, the specific factors underlying these abnormalities remain largely unknown. In this study, we aimed to investigate the role of a cardiac-specific long noncoding RNA, D830005E20Rik (Trdn-as), in DCM. Our results revealed the remarkably upregulation of Trdn-as in the hearts of the DCM mice and cardiomyocytes treated with high glucose (HG). Knocking down Trdn-as in cardiac tissues significantly improved cardiac dysfunction and remodeling in the DCM mice. Conversely, Trdn-as overexpression resulted in cardiac damage resembling that observed in the DCM mice. At the cellular level, Trdn-as induced Ca²⁺ overload in the SR and mitochondria, leading to mitochondrial dysfunction. RNA-seq and bioinformatics analyses identified calsequestrin 2 (Casq2), a primary calcium-binding protein in the junctional SR, as a potential target of Trdn-as. Further investigations revealed that Trdn-as facilitated the recruitment of METTL14 to the Casq2 mRNA, thereby enhancing the m⁶A modification of Casq2. This modification increased the stability of Casq2 mRNA and subsequently led to increased protein expression. When Casq2 was knocked down, the promoting effects of Trdn-as on Ca²⁺ overload and mitochondrial damage were mitigated. These findings provide valuable insights into the pathogenesis of DCM and suggest Trdn-as as a potential therapeutic target for this condition.
Animals ; Diabetic Cardiomyopathies/pathology* ; RNA, Long Noncoding/genetics* ; Myocytes, Cardiac/metabolism* ; Mice ; Calsequestrin/genetics* ; Calcium/metabolism* ; Male ; Sarcoplasmic Reticulum/metabolism* ; Methyltransferases/metabolism* ; Mice, Inbred C57BL ; Mitochondria, Heart/metabolism* ; Disease Models, Animal ; Mitochondria/metabolism*

The dysregulation of cyclin-dependent kinase 12 (CDK12), which may result from genomic alterations or modulation by upstream effectors, is implicated in cancer oncogenesis and progression. CDK12 overexpression or activation is sufficient to induce tumor initiation, recurrence, and therapeutic resistance. However, CDK12 may also exert tumor-suppressive functions in a context-dependent manner. Therefore, caution is warranted when targeting CDK12 in future clinical trials. A comprehensive elucidation of the dual roles and underlying mechanisms of CDK12 in carcinogenesis is urgently needed to advance precision oncology. This review provides an overview of the current understanding of the dysregulation and biological roles of CDK12 in cancer. Subsequently, we systematically summarize the functions and mechanisms of the oncogenic and tumor-suppressive roles of CDK12 in different contexts. Finally, we discuss the potential of CDK12 as a novel therapeutic target and its implications in clinical oncology, offering insights into future directions for innovative cancer treatment strategies.

Neuroscience is a significant frontier discipline within the natural sciences and has become an important interdisciplinary frontier scientific field. Brain is one of the most complex organs in the human body, and its structural and functional analysis is considered the “ultimate frontier” of human self-awareness and exploration of nature. Driven by the strategic layout of “China Brain Project”, Chinese scientists have conducted systematic research focusing on “understanding the brain, simulating the brain, and protecting the brain”. They have made breakthrough progress in areas such as the principles of brain cognition, mechanisms and interventions for brain diseases, brain-like computation, and applications of brain-machine intelligence technology, aiming to enhance brain health through biomedical technology and improve the quality of human life. Due to limited understanding and comprehension of neuroscience, there are still many important unresolved issues in the field of neuroscience, resulting in a lack of effective measures to prevent and protect brain health. Therefore, in addition to actively developing new generation drugs, exploring non pharmacological treatment strategies with better health benefits and higher safety is particularly important. Epidemiological data shows that, exercise is not only an indispensable part of daily life but also an important non-pharmacological approach for protecting brain health and preventing neurodegenerative diseases, forming an emerging research field known as motor neuroscience. Basic research in motor neuroscience primarily focuses on analyzing the dynamic coding mechanisms of neural circuits involved in motor control, breakthroughs in motor neuroscience research depend on the construction of dynamic monitoring systems across temporal and spatial scales. Therefore, high spatiotemporal resolution detection of movement processes and movement-induced changes in brain structure and neural activity signals is an important technical foundation for conducting motor neuroscience research and has developed a set of tools based on traditional neuroscience methods combined with novel motor behavior decoding technologies, providing an innovative technical platform for motor neuroscience research. The protective effect of exercise in neurodegenerative diseases provides broad application prospects for its clinical translation. Applied research in motor neuroscience centers on deciphering the regulatory networks of neuroprotective molecules mediated by exercise. From the perspectives of exercise promoting neurogenesis and regeneration, enhancing synaptic plasticity, modulating neuronal functional activity, and remodeling the molecular homeostasis of the neuronal microenvironment, it aims to improve cognitive function and reduce the incidence of Parkinson’s disease and Alzheimer’s disease. This has also advanced research into the molecular regulatory networks mediating exercise-induced neuroprotection and facilitated the clinical application and promotion of exercise rehabilitation strategies. Multidimensional analysis of exercise-regulated neural plasticity is the theoretical basis for elucidating the brain-protective mechanisms mediated by exercise and developing intervention strategies for neurological diseases. Thus,real-time analysis of different neural signals during active exercise is needed to study the health effects of exercise throughout the entire life cycle and enhance lifelong sports awareness. Therefore, this article will systematically summarize the innovative technological developments in motor neuroscience research, review the mechanisms of neural plasticity that exercise utilizes to protect the brain, and explore the role of exercise in the prevention and treatment of major neurodegenerative diseases. This aims to provide new ideas for future theoretical innovations and clinical applications in the field of exercise-induced brain protection.

Optical imaging is highly valued for its superior temporal and spatial resolution. This is particularly important in near-infrared II (NIR-II, 1 000-3 000 nm) imaging, which offers advantages such as reduced tissue absorption, minimal scattering, and low autofluorescence. These characteristics make NIR-II imaging especially suitable for deep tissue visualization, where high contrast and minimal background interference are critical for accurate diagnosis and monitoring. Currently, inorganic fluorescent probes—such as carbon nanotubes, rare earth nanoparticles, and quantum dots—offer high brightness and stability. However, they are hindered by ambiguous structures, larger sizes, and potential accumulation toxicity in vivo. In contrast, organic fluorescent probes, including small molecules and polymers, demonstrate higher biocompatibility but are limited by shorter emission wavelengths, lower quantum yields, and reduced stability. Recently, gold clusters have emerged as a promising class of nanomaterials with potential applications in biocatalysis, fluorescence sensing, biological imaging, and more. Water-soluble gold clusters are particularly attractive as fluorescent probes due to their remarkable optical properties, including strong photoluminescence, large Stokes shifts, and excellent photostability. Furthermore, their outstanding biocompatibility—attributed to good aqueous stability, ultra-small hydrodynamic size, and high renal clearance efficiency—makes them especially suitable for biomedical applications. Gold clusters hold significant potential for NIR-II fluorescence imaging. Atomic-precision gold clusters, typically composed of tens to hundreds of gold atoms and measuring only a few nanometers in diameter, possess well-defined three-dimensional structures and clear spatial coordination. This atomic-level precision enables fine-tuned structural regulation, further enhancing their fluorescence properties. Variations in cluster size, surface ligands, and alloying elements can result in distinct physicochemical characteristics. The incorporation of different atoms can modulate the atomic and electronic structures of gold clusters, while diverse ligands can influence surface polarity and steric hindrance. As such, strategies like alloying and ligand engineering are effective in enhancing both fluorescence and catalytic performance, thereby meeting a broader range of clinical needs. In recent years, gold clusters have attracted growing attention in the biomedical field. Their application in NIR-II imaging has led to significant progress in vascular, organ, and tumor imaging. The resulting high-resolution, high signal-to-noise imaging provides powerful tools for clinical diagnostics. Moreover, biologically active gold clusters can aid in drug delivery and disease diagnosis and treatment, offering new opportunities for clinical therapeutics. Despite the notable achievements in fundamental research and clinical translation, further studies are required to address challenges related to the standardized synthesis and complex metabolic behavior of gold clusters. Resolving these issues will help accelerate their clinical adoption and broaden their biomedical applications.