Chronic diabetic wounds, severely complicated by multidrug-resistant (MDR) bacterial infections, represent a profound and escalating global health crisis. The intrinsically hostile microenvironment of diabetic wounds, characterized by localized hypoxia, persistent oxidative stress, and poor vascularization, creates an ideal niche for opportunistic pathogens such as Staphylococcus aureus and Pseudomonas aeruginosa. These bacteria readily construct dense extracellular polymeric substance (EPS) biofilms, which not only physically shield the microbes from host immune responses but also actively trap the wound in a state of chronic, unresolved inflammation. Consequently, conventional systemic and topical antibiotic therapies are becoming increasingly futile, as poor perfusion at the wound site restricts drug bioavailability, while the rapid genetic evolution of bacteria and the impenetrable nature of biofilms lead to catastrophic treatment failures, often culminating in severe tissue necrosis and lower-extremity amputations. To circumvent the limitations of traditional antimicrobials, therapeutic gas delivery has emerged as a highly promising, paradigm-shifting strategy. Gaseous signaling molecules, particularly nitric oxide (NO), carbon monoxide (CO), hydrogen sulfide (H₂S), and hydrogen (H₂), possess unique physicochemical properties that allow them to seamlessly penetrate dense biofilm matrices and cellular membranes. Once inside, these gases operate via multi-targeted mechanisms that are incredibly difficult for bacteria to develop resistance against; for instance, NO induces severe lipid peroxidation and DNA cleavage in bacteria, CO downregulates pro-inflammatory cytokines, H₂S significantly accelerates endothelial cell migration for neovascularization, and H₂ acts as a powerful selective antioxidant to neutralize tissue-damaging reactive oxygen species (ROS). Together, these therapeutic gases not only exert broad-spectrum bactericidal effects but also actively reprogram the wound bed by promoting the critical M1-to-M2 macrophage polarization and stimulating angiogenesis. Despite their immense biological potential, the direct clinical translation of gas therapies is severely hindered by inherent physicochemical drawbacks, including extreme volatility, short physiological half-lives, poor aqueous solubility, and the high risk of off-target systemic toxicity, if applied indiscriminately. To conquer these immense pharmacokinetic barriers, cutting-edge advancements in materials science have driven the development of gas-releasing micro- and nanoplatforms. Utilizing sophisticated carriers such as metal-organic frameworks (MOFs), mesoporous silica, polymeric nanoparticles, liposomes, and injectable hydrogels, researchers can now encapsulate gas-donor molecules to achieve sustained, localized delivery. More importantly, these advanced nanoplatforms are ingeniously engineered to be stimuli-responsive. By exploiting the pathological hallmarks of the diabetic wound environment, such as elevated glucose concentrations, acidic pH, and overexpressed ROS, or by utilizing external triggers like near-infrared (NIR) light irradiation and ultrasound, these intelligent platforms ensure on-demand, precise spatio-temporal gas release. This often allows for powerful synergistic combinations, such as photothermal or photodynamic therapy coupled with gas release, thereby obliterating biofilms while sparing healthy tissue. While the therapeutic outcomes of these smart delivery systems in eradicating MDR infections and accelerating tissue repair are unprecedented, several critical challenges remain before widespread clinical adoption, as long-term biosafety profiles of the carrier nanomaterials, complexities in large-scale good manufacturing practice (GMP) production, and stringent regulatory hurdles must be rigorously addressed. Looking forward, the next frontier lies in the realm of precision medicine and theranostics, where future research must focus on the seamless integration of these gas-releasing platforms with flexible, wearable biosensors capable of continuously monitoring wound biomarkers (e.g., pH, temperature, uric acid) in real-time. Coupled with artificial intelligence algorithms to govern automated, closed-loop adaptive dosing, these next-generation smart dressings hold the ultimate potential to comprehensively transform the clinical management of complex, infected diabetic wounds.

Chronic diabetic wounds, severely complicated by multidrug-resistant (MDR) bacterial infections, represent a profound and escalating global health crisis. The intrinsically hostile microenvironment of diabetic wounds, characterized by localized hypoxia, persistent oxidative stress, and poor vascularization, creates an ideal niche for opportunistic pathogens such as Staphylococcus aureus and Pseudomonas aeruginosa. These bacteria readily construct dense extracellular polymeric substance (EPS) biofilms, which not only physically shield the microbes from host immune responses but also actively trap the wound in a state of chronic, unresolved inflammation. Consequently, conventional systemic and topical antibiotic therapies are becoming increasingly futile, as poor perfusion at the wound site restricts drug bioavailability, while the rapid genetic evolution of bacteria and the impenetrable nature of biofilms lead to catastrophic treatment failures, often culminating in severe tissue necrosis and lower-extremity amputations. To circumvent the limitations of traditional antimicrobials, therapeutic gas delivery has emerged as a highly promising, paradigm-shifting strategy. Gaseous signaling molecules, particularly nitric oxide (NO), carbon monoxide (CO), hydrogen sulfide (H₂S), and hydrogen (H₂), possess unique physicochemical properties that allow them to seamlessly penetrate dense biofilm matrices and cellular membranes. Once inside, these gases operate via multi-targeted mechanisms that are incredibly difficult for bacteria to develop resistance against; for instance, NO induces severe lipid peroxidation and DNA cleavage in bacteria, CO downregulates pro-inflammatory cytokines, H₂S significantly accelerates endothelial cell migration for neovascularization, and H₂ acts as a powerful selective antioxidant to neutralize tissue-damaging reactive oxygen species (ROS). Together, these therapeutic gases not only exert broad-spectrum bactericidal effects but also actively reprogram the wound bed by promoting the critical M1-to-M2 macrophage polarization and stimulating angiogenesis. Despite their immense biological potential, the direct clinical translation of gas therapies is severely hindered by inherent physicochemical drawbacks, including extreme volatility, short physiological half-lives, poor aqueous solubility, and the high risk of off-target systemic toxicity, if applied indiscriminately. To conquer these immense pharmacokinetic barriers, cutting-edge advancements in materials science have driven the development of gas-releasing micro- and nanoplatforms. Utilizing sophisticated carriers such as metal-organic frameworks (MOFs), mesoporous silica, polymeric nanoparticles, liposomes, and injectable hydrogels, researchers can now encapsulate gas-donor molecules to achieve sustained, localized delivery. More importantly, these advanced nanoplatforms are ingeniously engineered to be stimuli-responsive. By exploiting the pathological hallmarks of the diabetic wound environment, such as elevated glucose concentrations, acidic pH, and overexpressed ROS, or by utilizing external triggers like near-infrared (NIR) light irradiation and ultrasound, these intelligent platforms ensure on-demand, precise spatio-temporal gas release. This often allows for powerful synergistic combinations, such as photothermal or photodynamic therapy coupled with gas release, thereby obliterating biofilms while sparing healthy tissue. While the therapeutic outcomes of these smart delivery systems in eradicating MDR infections and accelerating tissue repair are unprecedented, several critical challenges remain before widespread clinical adoption, as long-term biosafety profiles of the carrier nanomaterials, complexities in large-scale good manufacturing practice (GMP) production, and stringent regulatory hurdles must be rigorously addressed. Looking forward, the next frontier lies in the realm of precision medicine and theranostics, where future research must focus on the seamless integration of these gas-releasing platforms with flexible, wearable biosensors capable of continuously monitoring wound biomarkers (e.g., pH, temperature, uric acid) in real-time. Coupled with artificial intelligence algorithms to govern automated, closed-loop adaptive dosing, these next-generation smart dressings hold the ultimate potential to comprehensively transform the clinical management of complex, infected diabetic wounds.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

The ventral anterior (VA) nucleus of the thalamus is a major target of the basal ganglia and is closely associated with the pathogenesis of Parkinson's disease (PD). Notably, the VA receives direct innervation from the hypothalamic histaminergic system. However, its role in PD remains unknown. Here, we assessed the contribution of histamine to VA neuronal activity and PD motor deficits. Functional magnetic resonance imaging showed reduced VA activity in PD patients. Optogenetic activation of VA neurons or histaminergic afferents significantly alleviated motor deficits in 6-OHDA-induced PD rats. Furthermore, histamine excited VA neurons via H1 and H2 receptors and their coupled hyperpolarization-activated cyclic nucleotide-gated channels, inward-rectifier K⁺ channels, or Ca²⁺-activated K⁺ channels. These results demonstrate that histaminergic afferents actively compensate for Parkinsonian motor deficits by biasing VA activity. These findings suggest that targeting VA histamine receptors and downstream ion channels may be a potential therapeutic strategy for PD motor dysfunction.
Animals ; Histamine/metabolism* ; Male ; Oxidopamine/toxicity* ; Rats ; Ventral Thalamic Nuclei/physiopathology* ; Rats, Sprague-Dawley ; Disease Models, Animal ; Parkinson Disease/metabolism* ; Neurons/physiology* ; Humans ; Optogenetics

Chronic cerebral hypoperfusion leads to white matter injury (WMI), which plays a significant role in contributing to vascular cognitive impairment. While 13-docosenamide is a type of fatty acid amide, it remains unclear whether it has therapeutic effects on chronic cerebral hypoperfusion. In this study, we conducted bilateral common carotid artery stenosis (BCAS) surgery to simulate chronic cerebral hypoperfusion-induced WMI and cognitive impairment. Our findings showed that 13-docosenamide alleviates WMI and cognitive impairment in BCAS mice. Mechanistically, 13-docosenamide specifically binds to cannabinoid receptor 1 (CNR1) in oligodendrocyte precursor cells (OPCs). This interaction results in an upregulation of ubiquitin-specific peptidase 33 (USP33)-mediated CNR1 deubiquitination, subsequently increasing CNR1 protein expression, activating the phosphorylation of the AKT/mTOR pathway, and promoting the differentiation of OPCs. In conclusion, our study suggests that 13-docosenamide can ameliorate chronic cerebral hypoperfusion-induced WMI and cognitive impairment by enhancing OPC differentiation and could serve as a potential therapeutic drug.
Animals ; Oligodendrocyte Precursor Cells/metabolism* ; Mice ; Cell Differentiation/drug effects* ; Male ; Receptor, Cannabinoid, CB1/metabolism* ; Mice, Inbred C57BL ; Ubiquitin Thiolesterase/metabolism* ; Ubiquitination/drug effects* ; Carotid Stenosis/complications* ; Cognitive Dysfunction/drug therapy*

OBJECTIVE: Resveratrol (Res) is a promising anticancer drug against hepatocellular carcinoma (HCC), but whether its anti-HCC effects implicate mitophagy remains unclear. Therefore, we aimed to explore the specific role of Res in mitophagy and the related mechanisms during the treatment of HCC. METHODS: HepG2 cells and tumor-grafted nude mice were used to investigate the effects of low-, middle- and high-dose of Res on HCC progression and mitophagy in vitro and in vivo, respectively. A series of approaches including cell counting kit-8, flow cytometry, wound healing and transwell assays were used to evaluate tumor cell functions. Transmission electron microscopy, immunofluorescence and Western blotting were used to assess mitophagy. Mitochondrial oxygen consumption rate, reactive oxygen species and membrane potential were used to reflect mitochondrial function. After disrupting the expression of metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), miR-143-3p, and ribonucleoside reductase M2 (RRM2), the effects of the MALAT1/miR-143-3p/RRM2 axis on cell function and mitophagy under Res treatment were explored in vitro. Additionally, dual-luciferase reporter and chromatin immunoprecipitation were used to confirm interactions between target genes. RESULTS: Res significantly inhibited the proliferation and promoted apoptosis of HCC cells in vitro, while significantly suppressing tumor growth in a dose-dependent manner and inducing mitophagy and mitochondrial dysfunction in vivo. Interestingly, MALAT1 was highly expressed in HCC cells and its knockdown upregulated miR-143-3p expression in HCC cells, which subsequently inhibited RRM2 expression. Furthermore, in nude mice grafted with HCC tumors and treated with Res, the expression of MALAT1, miR-143-3p and RRM2 were altered significantly. In vitro data further supported the targeted binding relationships between MALAT1 and miR-143-3p and between miR-143-3p and RRM2. Therefore, a series of cell-based experiments were carried out to study the mechanism of the MALAT1/miR-143-3p/RRM2 axis involved in mitophagy and HCC; these experiments revealed that MALAT1 knockdown, miR-143-3p mimic and RRM silencing potentiated the antitumor effects of Res and its activation of mitophagy. CONCLUSION Res facilitated mitophagy in HCC and exerted anti-cancer effects by targeting the MALAT1/miR-143-3p/RRM2 axis. Please cite this article as: Feng CY, Cai CS, Shi XQ, Zhang ZJ, Su D, Qiu YQ. Resveratrol promotes mitophagy via the MALAT1/miR-143-3p/RRM2 axis and suppresses cancer progression in hepatocellular carcinoma. J Integr Med. 2025; 23(1): 79-91.
Humans ; MicroRNAs/genetics* ; Liver Neoplasms/metabolism* ; Carcinoma, Hepatocellular/metabolism* ; Mitophagy/drug effects* ; Resveratrol/pharmacology* ; Animals ; Mice, Nude ; RNA, Long Noncoding/genetics* ; Hep G2 Cells ; Mice ; Disease Progression ; Mice, Inbred BALB C

Microglia, the resident immune cells in the central nervous system (CNS), rapidly transition from a resting to an active state in the acute phase of ischemic brain injury. This active state mediates a pro-inflammatory response that can exacerbate the injury. Targeting the pro-inflammatory response of microglia in the semi-dark band during this acute phase may effectively reduce brain injury. Shionone (SH), an active ingredient extracted from the dried roots and rhizomes of the genus Aster (Asteraceae), has been reported to regulate the inflammatory response of macrophages in sepsis-induced acute lung injury. However, its function in post-stroke neuroinflammation, particularly microglia-mediated neuroinflammation, remains uninvestigated. This study found that SH significantly inhibited lipopolysaccharide (LPS)-induced elevation of inflammatory cytokines, including interleukin-1β (IL-1β), tumor necrosis factor-α (TNF-α), and inducible nitric oxide synthase (iNOS), in microglia in vitro. Furthermore, the results demonstrated that SH alleviated infarct volume and improved behavioral performance in middle cerebral artery occlusion (MCAO) mice, which may be attributed to the inhibition of the microglial inflammatory response induced by SH treatment. Mechanistically, SH potently inhibited the phosphorylation of serine-threonine protein kinase B (AKT), mammalian target of rapamycin (mTOR), and signal transducer and activator of transcription 3 (STAT3). These findings suggest that SH may be a potential therapeutic agent for relieving ischemic stroke (IS) by alleviating microglia-associated neuroinflammation.
Animals ; Microglia/immunology* ; Mice ; Male ; Mice, Inbred C57BL ; Brain Ischemia/immunology* ; Neuroinflammatory Diseases/drug therapy* ; Neuroprotective Agents/administration & dosage* ; Interleukin-1beta/genetics* ; STAT3 Transcription Factor/genetics* ; TOR Serine-Threonine Kinases/genetics* ; Tumor Necrosis Factor-alpha/genetics* ; Proto-Oncogene Proteins c-akt/immunology* ; Nitric Oxide Synthase Type II/genetics* ; Lipopolysaccharides

OBJECTIVE: To investigate the associations between eight serum per- and polyfluoroalkyl substances (PFASs) and regional fat depots, we analyzed the data from the National Health and Nutrition Examination Survey (NHANES) 2011-2018 cycles. METHODS: Multiple linear regression models were developed to explore the associations between serum PFAS concentrations and six fat compositions along with a fat distribution score created by summing the concentrations of the six fat compositions. The associations between structurally grouped PFASs and fat distribution were assessed, and a prediction model was developed to estimate the ability of PFAS exposure to predict obesity risk. RESULTS: Among females aged 39-59 years, trunk fat mass was positively associated with perfluorooctane sulfonate (PFOS). Higher concentrations of PFOS, perfluorohexane sulfonate (PFHxS), perfluorodecanoate (PFDeA), perfluorononanoate (PFNA), and n-perfluorooctanoate (n-PFOA) were linked to greater visceral adipose tissue in this group. In men, exposure to total perfluoroalkane sulfonates (PFSAs) and long-chain PFSAs was associated with reductions in abdominal fat, while higher abdominal fat in women aged 39-59 years was associated with short-chain PFSAs. The prediction model demonstrated high accuracy, with an area under the curve (AUC) of 0.9925 for predicting obesity risk. CONCLUSION PFAS exposure is associated with regional fat distribution, with varying effects based on age, sex, and PFAS structure. The findings highlight the potential role of PFAS exposure in influencing fat depots and obesity risk, with significant implications for public health. The prediction model provides a highly accurate tool for assessing obesity risk related to PFAS exposure.
Humans ; Fluorocarbons/blood* ; Female ; Adult ; Middle Aged ; Male ; Environmental Pollutants/blood* ; Abdominal Fat ; Nutrition Surveys ; Alkanesulfonic Acids/blood* ; Obesity ; Environmental Exposure

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.