Development and validation of a novel nomogram model for predicting delayed graft function in deceased donor kidney transplantation based on pre-transplant biopsies.

BACKGROUND: Delayed graft function (DGF) is an important complication after kidney transplantation surgery. The present study aimed to develop and validate a nomogram for preoperative prediction of DGF on the basis of clinical and histological risk factors. METHODS: The prediction model was constructed in a development cohort comprising 492 kidney transplant recipients from May 2018 to December 2019. Data regarding donor and recipient characteristics, pre-transplantation biopsy results, and machine perfusion parameters were collected, and univariate analysis was performed. The least absolute shrinkage and selection operator regression model was used for variable selection. The prediction model was developed by multivariate logistic regression analysis and presented as a nomogram. An external validation cohort comprising 105 transplantation cases from January 2020 to April 2020 was included in the analysis. RESULTS: 266 donors were included in the development cohort, 458 kidneys (93.1%) were preserved by hypothermic machine perfusion (HMP), 96 (19.51%) of 492 recipients developed DGF. Twenty-eight variables measured before transplantation surgery were included in the LASSO regression model. The nomogram consisted of 12 variables from donor characteristics, pre-transplantation biopsy results and machine perfusion parameters. Internal and external validation showed good discrimination and calibration of the nomogram, with Area Under Curve (AUC) 0.83 (95%CI, 0.78-0.88) and 0.87 (95%CI, 0.80-0.94). Decision curve analysis demonstrated that the nomogram was clinically useful. CONCLUSION: A DGF predicting nomogram was developed that incorporated donor characteristics, pre-transplantation biopsy results, and machine perfusion parameters. This nomogram can be conveniently used for preoperative individualized prediction of DGF in kidney transplant recipients.

Precision Prediction for Dengue Fever in Singapore: A Machine Learning Approach Incorporating Meteorological Data.

OBJECTIVE: This study aimed to improve dengue fever predictions in Singapore using a machine learning model that incorporates meteorological data, addressing the current methodological limitations by examining the intricate relationships between weather changes and dengue transmission. METHOD: Using weekly dengue case and meteorological data from 2012 to 2022, the data was preprocessed and analyzed using various machine learning algorithms, including General Linear Model (GLM), Support Vector Machine (SVM), Gradient Boosting Machine (GBM), Decision Tree (DT), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) algorithms. Performance metrics such as Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and R-squared (R2) were employed. RESULTS: From 2012 to 2022, there was a total of 164,333 cases of dengue fever. Singapore witnessed a fluctuating number of dengue cases, peaking notably in 2020 and revealing a strong seasonality between March and July. An analysis of meteorological data points highlighted connections between certain climate variables and dengue fever outbreaks. The correlation analyses suggested significant associations between dengue cases and specific weather factors such as solar radiation, solar energy, and UV index. For disease predictions, the XGBoost model showed the best performance with an MAE = 89.12, RMSE = 156.07, and R2 = 0.83, identifying time as the primary factor, while 19 key predictors showed non-linear associations with dengue transmission. This underscores the significant role of environmental conditions, including cloud cover and rainfall, in dengue propagation. CONCLUSION: In the last decade, meteorological factors have significantly influenced dengue transmission in Singapore. This research, using the XGBoost model, highlights the key predictors like time and cloud cover in understanding dengue's complex dynamics. By employing advanced algorithms, our study offers insights into dengue predictive models and the importance of careful model selection. These results can inform public health strategies, aiming to improve dengue control in Singapore and comparable regions.

Exploring the optimal indicator of short-term peridiagnosis weight dynamics to predict cancer survival: A multicentre cohort study.

BACKGROUND: Body weight and its changes have been associated with cancer outcomes. However, the associations of short-term peridiagnosis weight dynamics in standardized, clinically operational time frames with cancer survival remain largely unknown. This study aimed to screen for and evaluate the optimal indicator of short-term peridiagnosis weight dynamics to predict overall survival (OS) in patients with cancer. METHODS: This multicentre cohort study prospectively collected data from 7460 patients pathologically diagnosed with cancer between 2013 and 2019. Body weight data were recorded 1 month before, at the time of and 1 month following diagnosis. By permuting different types (point value in kg, point height-adjusted value in kg/m2, absolute change in kg or relative change in percentage) and time frames (prediagnosis, postdiagnosis or peridiagnosis), we generated 12 different weight-related indicators and compared their prognostic performance using Harrell's C-index, integrated discrimination improvement, continuous net reclassification improvement and time-dependent C-index. We analysed associations of peridiagnosis relative weight change (RWC) with OS using restricted cubic spine (RCS), Kaplan-Meier analysis and multivariable-adjusted Cox regression models. RESULTS: The study enrolled 5012 males and 2448 females, with a median age of 59 years. During a median follow-up of 37 months, 1026 deaths occurred. Peridiagnosis (1 month before diagnosis to 1 month following diagnosis) RWC showed higher prognostic performance (Harrell's C-index = 0.601, 95% confidence interval [CI] = [0.583, 0.619]) than other types of indicators including body mass index (BMI), absolute weight change, absolute BMI change, prediagnosis RWC and postdiagnosis RWC in the study population (all P < 0.05). Time-dependent C-index analysis also indicated that peridiagnosis RWC was optimal for predicting OS. The multivariable-adjusted RCS analysis revealed an N-shaped non-linear association between peridiagnosis RWC and OS (PRWC < 0.001, Pnon-linear < 0.001). Univariate survival analysis showed that the peridiagnosis RWC groups could represent distinct mortality risk stratifications (P < 0.001). Multivariable survival analysis showed that, compared with the maintenance group (weight change < 5%), the significant (gain >10%, hazard ratio [HR] = 0.530, 95% CI = [0.413, 0.680]) and moderate (gain 5-10%, HR = 0.588, 95% CI = [0.422, 0.819]) weight gain groups were both associated with improved OS. In contrast, the moderate (loss 5-10%, HR = 1.219, 95% CI = [1.029, 1.443]) and significant (loss >10%, HR = 1.280, 95% CI = [1.095, 1.497]) weight loss groups were both associated with poorer OS. CONCLUSIONS: The prognostic performance of peridiagnosis RWC is superior to other weight-related indicators in patients with cancer. The findings underscore the importance of expanding the surveillance of body weight from at diagnosis to both past and future, and conducting it within clinically operational time frames, in order to identify and intervene with patients who are at risk of weight change-related premature deaths.

Local symmetry-driven interfacial magnetization and electronic states in (ZnO)n/(w-FeO)n superlattices.

Superlattices constructed with the wide-band-gap semiconductor ZnO and magnetic oxide FeO, both in the wurtzite structure, have been investigated using spin-polarized first-principles calculations. The structural, electronic and magnetic properties of the (ZnO)n/(w-FeO)n superlattices were studied in great detail. Two different interfaces in the (ZnO)n/(w-FeO)n superlattices were identified and they showed very different magnetic and electronic properties. Local symmetry-driven interfacial magnetization and electronic states can arise from different Fe/Zn distributions at different interfaces or spin ordering of Fe in the superlattice. The local symmetry-driven interfacial magnetization and electronic states, originating either from different Fe/Zn distribution across interfaces I and II, or by spin ordering of Fe in the superlattice, can be identified. It was also found that, in the case of the ferromagnetic phase, the electrons are more delocalized for the majority spin but strongly localized for the minority spin, which resulted in interesting spin-dependent transport properties. Our results will pave the way for designing novel spin-dependent electronic devices through the construction of superlattices from semiconductors and multiferroics.

12,13-diHOME attenuates high glucose-induced calcification of vascular smooth muscle cells through repressing CPT1A-mediated HMGB1 succinylation.

Diabetes is closely associated with vascular calcification (VC). Exorbitant glucose concentration activates pro-calcific effects in vascular smooth muscle cells (VSMCs). This study enrolled 159 elderly patients with type 2 diabetes and divided them into three groups, T1, T2 and T3, according to brachial-ankle pulse wave velocity(BaPWV). There were statistically significant differences in the waist circumference, waist hip ratio, systolic blood pressure, 12,13-diHOME (a lipokin) concentration among T1, T2 and T3. 12,13-diHOME levels were positively correlated to high density lipoprotein cholesterol and total cholesterol, but negatively correlated to with waist circumference, waist hip ratio, systolic blood pressure and baPWV. Studies in vitro showed that 12,13-diHOME effectively inhibits calcification in VSMCs under high glucose conditions. Notably, 12,13-diHOME suppressed the up-regulation of carnitine O-palmitoyltransferase 1 (CPT1A) and CPT1A-induced succinylation of HMGB1. The succinylation of HMGB1 at the K90 promoted the protein stability and induced the enrichment of HMGB1 in cytoplasm, which induced the calcification in VSMCs. Together, 12,13-diHOME attenuates high glucose-induced calcification in VSMCs through repressing CPT1A-mediated HMGB1 succinylation.

Hidden diversity and potential ecological function of phosphorus acquisition genes in widespread terrestrial bacteriophages.

Phosphorus (P) limitation of ecosystem processes is widespread in terrestrial habitats. While a few auxiliary metabolic genes (AMGs) in bacteriophages from aquatic habitats are reported to have the potential to enhance P-acquisition ability of their hosts, little is known about the diversity and potential ecological function of P-acquisition genes encoded by terrestrial bacteriophages. Here, we analyze 333 soil metagenomes from five terrestrial habitat types across China and identify 75 viral operational taxonomic units (vOTUs) that encode 105 P-acquisition AMGs. These AMGs span 17 distinct functional genes involved in four primary processes of microbial P-acquisition. Among them, over 60% (11/17) have not been reported previously. We experimentally verify in-vitro enzymatic activities of two pyrophosphatases and one alkaline phosphatase encoded by P-acquisition vOTUs. Thirty-six percent of the 75 P-acquisition vOTUs are detectable in a published global topsoil metagenome dataset. Further analyses reveal that, under certain circumstances, the identified P-acquisition AMGs have a greater influence on soil P availability and are more dominant in soil metatranscriptomes than their corresponding bacterial genes. Overall, our results reinforce the necessity of incorporating viral contributions into biogeochemical P cycling.

The value of LCI-based modified Kyoto classification risk scoring system in predicting the risk of early gastric cancer.

OBJECTIVE: To study and compare the value of the Kyoto classification risk scoring system and the modified Kyoto classification risk scoring system based on linked color imaging (LCI) in predicting the risk of early gastric cancer. METHODS: One hundred and fifty patients with pathologically confirmed non-cardia early gastric cancer by endoscopic LCI and 150 non-gastric cancer patients matched for age and gender were included. Basic patient data and whole gastric endoscopic images under LCI were collected, and the images were scored according to the LCI-based Kyoto classification risk scoring system and the LCI-based modified Kyoto classification risk scoring system. RESULTS: Compared with the LCI-based Kyoto classification risk scoring system, the LCI-based modified Kyoto classification risk scoring system had a higher AUC for predicting the risk of early gastric cancer (0.723 vs. 0.784, p = 0.023), with a score of ≥3 being the best cutoff value for predicting the risk of early gastric cancer (sensitivity 61.33%, specificity 86.00%), and scores of 3 to 5 were significantly associated with early gastric carcinogenesis significantly (OR = 9.032, 95% CI: 4.995-16.330, p < 0.001). CONCLUSIONS: Compared with the LCI-based Kyoto classification risk scoring system, the LCI-based Kyoto modified classification risk scoring system has a better value for predicting the risk of early gastric cancer, and the score of 3 to 5 is a high-risk factor for the risk of early gastric cancer development, which is more strongly correlated with the risk of early gastric cancer.

The status of nuclear medicine in China: the first official national survey.

AIM/INTRODUCTION: The National Nuclear Medicine Quality Control Center of China conducted the first official survey to investigate the nationwide situation of nuclear medicine in 2020. The survey aimed to unveil the current nuclear medicine situation and its quality control in China. MATERIALS AND METHODS: The web-based survey was conducted and the data was collected via the National Clinical Improvement System (NCIS) of China from 1st April to 31st May 2021. RESULTS: A total of 808 institutes across 30 provinces responded to the national survey. For human resources, there are 4460 physicians, 3077 technologists, 339 physicists, and 309 radiochemists. There are 887 single-photon imaging instruments, including 823 SPECT or SPECT/CT, and 365 PET instruments including 314 PET/CT. Six hundred twenty-four institutes perform SPECT examinations and 319 institutes perform PET examinations. 60% of SPECT scans are bone scintigraphy. A total of 97% of PET scans use an [18F]F-FDG tracer. Furthermore, 587 institutes provide radionuclide therapy services but only 280 institutes have admission rooms. The top three radionuclide therapies are [131I] therapy of hyperthyroidism with 546 institutes, [89Sr] therapy of bone metastasis with 400 institutes, and [131I] therapy of differentiated thyroid cancer with 286 institutes. Finally, for the frequency of equipment quality control per year, there are about 67 times self-test within the department for SPECT instruments and 111 times for PET instruments on average in each province. There are about three failures of SPECT and five failures of PET on average per year in each province. There are 408 institutes (of 624 SPECT institutes) performing quality control of SPECT radiopharmaceuticals, 216 (of 319) for PET radiopharmaceuticals, and 373 (of 587) for radionuclide therapy. CONCLUSION: These results of the first official survey towards current status of nuclear medicine in China are the foundation for the establishment of the quality control management system.

Fluorocarbon Nanodroplets: Their Formation and Stability in Complex Solution Systems.

Perfluorocarbon (PFC) nanodroplets (NDs) are expanding in a wide range of applications in biotechnology and nanotechnology. Their efficacy in biological systems is significantly influenced by their size uniformity and stability within bioelectrolyte contexts. Presently, methods for creating monodisperse, highly concentrated, and well-stabilized PFC NDs under harsh conditions using low energy consumption methods have not been thoroughly developed, and their stability has not been sufficiently explored. This gap restricts their applicability for advanced medical interventions in tissues with high pH levels and various electrolytic conditions. To tackle these challenges and to circumvent potential toxicity from surface stabilizers, we have conducted an in-depth investigation into the formation and stability of uncoated perfluorohexane (PFH) NDs, which were synthesized by using a low-energy consumption solvent exchange technique, across complex electrolyte compositions or a broad spectrum of pH levels. The results indicated that low concentrations of low-valent electrolyte ions facilitate the nucleation of NDs and consistently accelerate Ostwald ripening over an extended period. Conversely, high concentrations of highly valent electrolyte ions inhibit nucleation and decelerate the ripening process over time. Given the similarities between the properties of NDs and nanobubbles, we propose a potential stabilization mechanism. Electrolytes influence the Ostwald ripening of NDs by adjusting the adsorption and distribution of ions on the NDs' surface, modifying the thickness of the electric double layer, and fine-tuning the energy barrier between droplets. These insights enable precise control over the stability of PFC NDs through the meticulous adjustment of the surrounding electrolyte composition. This offers an effective preparation method and a theoretical foundation for employing bare PFC NDs in physiological settings.

A Quantum Spatial Graph Convolutional Neural Network Model on Quantum Circuits.

This article proposes a quantum spatial graph convolutional neural network (QSGCN) model that is implementable on quantum circuits, providing a novel avenue to processing non-Euclidean type data based on the state-of-the-art parameterized quantum circuit (PQC) computing platforms. Four basic blocks are constructed to formulate the whole QSGCN model, including the quantum encoding, the quantum graph convolutional layer, the quantum graph pooling layer, and the network optimization. In particular, the trainability of the QSGCN model is analyzed through discussions on the barren plateau phenomenon. Simulation results from various types of graph data are presented to demonstrate the learning, generalization, and robustness capabilities of the proposed quantum neural network (QNN) model.

The novel HLA-DPB1*1500:01N allele, identified by Sanger dideoxy nucleotide sequencing in a Chinese individual.

HLA-DPB1*1500:01N differs from HLA-DPB1*05:01:01:01 by one nucleotide in exon 3.

Effects of warming on soil organic carbon pools mediated by mycorrhizae and hyphae on the Eastern Tibetan Plateau, China.

Mycorrhizae and their hyphae play critical roles in soil organic carbon (SOC) accumulation. However, their individual contributions to SOC components and stability under climate warming conditions remain unclear. This study investigated the effects of warming on the SOC pools of Picea asperata (an ectomycorrhizal plant) and Fargesia nitida (an arbuscular mycorrhizal plant) mycorrhizae/hyphae on the eastern Tibetan Plateau. The results indicated that mycorrhizae made greater contributions to SOC accumulation than hyphae did by increasing labile organic carbon (LOC) components, such as particle organic carbon (POC), easily oxidizable organic carbon, and microbial biomass carbon, especially under warming conditions. Plant species also had different effects on SOC composition, resulting in higher mineral-associated organic carbon (MAOC) contents in F. nitida plots than in P. asperata plots; consequently, the former favored SOC stability more than the latter, with a lower POC/MAOC. Partial least-squares path modelling further indicated that mycorrhizae/hyphae indirectly affected LOC pools, mainly by changing soil pH and enzyme activities. Warming had no significant effect on SOC content but did change SOC composition by reducing LOC through affecting soil pH and iron oxides and ultimately increasing SOC stability in the presence of mycorrhizae for both plants. Therefore, the mycorrhizae of both plants are major contributors to the variation of SOC components and stability under warming conditions.

Easy but Efficient: Facile Approach to Molecule with Theoretically Justified Donor-Acceptor Structure for Effective Photothermal Conversion and Intravenous Photothermal Therapy.

To accelerate the pace in the field of photothermal therapy (PTT), it is urged to develop easily accessible photothermal agents (PTAs) showing high photothermal conversion efficiency (PCE). As a proof-of-concept, hereby a conventional strategy is presented to prepare donor-acceptor (D-A) structured PTAs through cycloaddition-retroelectrocyclization (CA-RE) reaction, and the resultant PTAs give high PCE upon near-infrared (NIR) irradiation. By joint experimental-theoretical study, these PTAs exhibit prominent D-A structure with strong intramolecular charge transfer (ICT) characteristics and significantly twisting between D and A units which account for the high PCEs. Among them, the DMA-TCNQ exhibits the strongest absorption in NIR range as well as the highest PCE of 91.3% upon irradiation by 760-nm LED lamp (1.2 W cm-2 ). In vitro and in vivo experimental results revealed that DMA-TCNQ exhibits low dark toxicity and high phototoxicity after IR irradiation along with nude mice tumor inhibition up to 81.0% through intravenous therapy. The findings demonstrate CA-RE reaction as a convenient approach to obtain twisted D-A structured PTAs for effective PTT and probably promote the progress of cancer therapies.

Natural variables separate the endemic areas of Clonorchis sinensis and Opisthorchis viverrini along a continuous, straight zone in Southeast Asia.

BACKGROUND: Clonorchiasis and opisthorchiasis, caused by the liver flukes Clonorchis sinensis and Opisthorchis viverrini respectively, represent significant neglected tropical diseases (NTDs) in Asia. The co-existence of these pathogens in overlapping regions complicates effective disease control strategies. This study aimed to clarify the distribution and interaction of these diseases within Southeast Asia. METHODS: We systematically collated occurrence records of human clonorchiasis (n = 1809) and opisthorchiasis (n = 731) across the Southeast Asia countries. Utilizing species distribution models incorporating environmental and climatic data, coupled machine learning algorithms with boosted regression trees, we predicted and distinguished endemic areas for each fluke species. Machine learning techniques, including geospatial analysis, were employed to delineate the boundaries between these flukes. RESULTS: Our analysis revealed that the endemic range of C. sinensis and O. viverrini in Southeast Asia primarily spans across part of China, Vietnam, Thailand, Laos, and Cambodia. During the period from 2000 to 2018, we identified C. sinensis infections in 84 distinct locations, predominantly in southern China (Guangxi Zhuang Autonomous Region) and northern Vietnam. In a stark contrast, O. viverrini was more widely distributed, with infections documented in 721 locations across Thailand, Laos, Cambodia, and Vietnam. Critical environmental determinants were quantitatively analyzed, revealing annual mean temperatures ranging between 14 and 20 °C in clonorchiasis-endemic areas and 24-30 °C in opisthorchiasis regions (P < 0.05). The machine learning model effectively mapped a distinct demarcation zone, demonstrating a clear separation between the endemic areas of these two liver flukes with AUC from 0.9 to1. The study in Vietnam delineates the coexistence and geographical boundaries of C. sinensis and O. viverrini, revealing distinct endemic zones and a transitional area where both liver fluke species overlap. CONCLUSIONS: Our findings highlight the critical role of specific climatic and environmental factors in influencing the geographical distribution of C. sinensis and O. viverrini. This spatial delineation offers valuable insights for integrated surveillance and control strategies, particularly in regions with sympatric transmission. The results underscore the need for tailored interventions, considering regional epidemiological variations. Future collaborations integrating eco-epidemiology, molecular epidemiology, and parasitology are essential to further elucidate the complex interplay of liver fluke distributions in Asia.

Characteristics of lymphocyte subsets and inflammatory factors in patients with COVID-19.

Objective: This research aims to examine the involvement of lymphocyte subsets and inflammatory cytokines in the development and progression of COVID-19. Methods: 164 COVID-19 patients were admitted to hospital between December 2022 and January 2023. Based on lung CT scans and whether it is necessary for intensive care unit (ICU) admission, they were categorized into: severe groups (84) and mild disease groups (80). Peripheral blood were also collected from 101 healthy examinees and 164 patients. Flow cytometry (FCM) was used to measure the absolute and relative counts of lymphocyte subsets, while chemiluminescence was used to detect the level of inflammatory cytokines. Results: The COVID-19 patient group exhibited lower count of lymphocytes subsets than healthy control group. Moreover, COVID-19 patient case presented higher content of cytokines (IL-6, IL-4, IL-8, IL-10, and TNF-α) expression compared to healthy control case. Within the COVID-19 patient group, individuals with severe disease showed lower counts of lymphocytes subsets than the mild disease case. Furthermore, IL-6 levels in severe case were higher than the mild disease patients case. Multi-variate logistic regression analysis confirmed IL-6 (odds ratio: 0.985 [0.977-0.993]), CD3+ T cells (odds ratio:1.007 [1.004-1.010]), CD8+ T cells (odds ratio:1.016 [1.009-1.023]), and CD19+ B cells (odds ratio:1.011 [1.002-1.020]) independently predicted severe progression. ROC curve results indicated AUC for lymphocytes in patients with severe COVID-19 was 0.8686 (0.8112-0.9260), CD3+ T cells was 0.8762 (0.8237-0.9287), CD8+ T cells was 0.7963 (0.7287-0.8638), CD4+ T cells was 0.8600 (0.8036-0.9164), CD19+ B cells was 0.7217 (0.6434-0.8001), NK cells was 0.6492 (0.5627-0.7357), age was 0.6699 (0.5877-0.7521), diabetes was 0.5991 (0.5125-0.6857), and IL-6 was 0.7241 (0.6479-0.8003). Furthermore, the ROC curves for different factors (CD3+ T cells, age, IL-6) yielded an AUC of 0.9031 (0.8580-0.9483). Conclusions: The research indicated that COVID-19 patients experience a decrease in lymphocytes subset and an increase in the inflammatory factor IL-6, particularly in the severe case group. As a result, the count of lymphocyte subset (CD3+ T cells) and the content of inflammatory cytokine (IL-6) can serve as predictive markers for assessing the severity of COVID-19 and developing treatment plans efficacy.

Effects of Nanobubbles on Photochemical Processes of Levofloxacin Photosensitizer.

Photodynamic therapy (PDT) stands as an efficacious modality for the treatment of cancer and various diseases, in which optimization of the electron transfer and augmentation of the production of lethal reactive oxygen species (ROS) represent pivotal challenges to enhance its therapeutic efficacy. Empirical investigations have established that the spontaneous initiation of redox reactions associated with electron transfer is feasible and is located in the gas-liquid interfaces. Meanwhile, nanobubbles (NBs) are emerging as entities capable of furnishing a plethora of such interfaces, attributed to their stability and large surface/volume ratio in bulk water. Thus, NBs provide a chance to expedite the electron-transfer kinetics within the context of PDT in an ambient environment. In this paper, we present a pioneering exploration into the impact of nitrogen nanobubbles (N2-NBs) on the electron transfer of the photosensitizer levofloxacin (LEV). Transient absorption spectra and time-resolved decay spectra, as determined through laser flash photolysis, unequivocally reveal that N2-NBs exhibit a mitigating effect on the decay of the LEV excitation triplet state, thereby facilitating subsequent processes. Of paramount significance is the observation that the presence of N2-NBs markedly accelerates the electron transfer of LEV, albeit with a marginal inhibitory influence on its energy-transfer reaction. This observation is corroborated through absorbance measurements and offers compelling evidence substantiating the role of NBs in expediting electron transfer within the ambit of PDT. The mechanism elucidated herein sheds light on how N2-NBs intricately influence both electron-transfer and energy-transfer reactions in the photosensitizer LEV. These findings not only contribute to a nuanced understanding of the underlying processes but also furnish novel insights that may inform the application of NBs in the realm of photodynamic therapy.

TGF-ß1/SMAD3-driven GLI2 isoform expression contributes to aggressive phenotypes of hepatocellular carcinoma.

Hedgehog signaling is activated in response to liver injury, and modulates organogenesis. However, the role of non-canonical hedgehog activation via TGF-ß1/SMAD3 in hepatic carcinogenesis is poorly understood. TGF-ß1/SMAD3-mediated non-canonical activation was found in approximately half of GLI2-positive hepatocellular carcinoma (HCC), and two new GLI2 isoforms with transactivating activity were identified. Phospho-SMAD3 interacted with active GLI2 isoforms to transactivate downstream genes in modulation of stemness, epithelial-mesenchymal transition, chemo-resistance and metastasis in poorly-differentiated hepatoma cells. Non-canonical activation of hedgehog signaling was confirmed in a transgenic HBV-associated HCC mouse model. Inhibition of TGF-ß/SMAD3 signaling reduced lung metastasis in a mouse in situ hepatic xenograft model. In another cohort of 55 HCC patients, subjects with high GLI2 expression had a shorter disease-free survival than those with low expression. Moreover, co-positivity of GLI2 with SMAD3 was observed in 87.5% of relapsed HCC patients with high GLI2 expression, indicating an increased risk of post-resection recurrence of HCC. The findings underscore that suppressing the non-canonical hedgehog signaling pathway may confer a potential strategy in the treatment of HCC.

Effects of electroacupuncture on the PI3K/Akt/CREB signaling pathway and hippocampal neuronal apoptosis in diabetic cognitive impairment rats. / ç”µé’ˆå¯¹ç³–å°¿ç— è®¤çŸ¥åŠŸèƒ½éšœç¢å¤§é¼ PI3K/Akt/CREBä¿¡å·é€šè·¯å’Œæµ·é©¬ç¥žç»å ƒå‡‹äº¡çš„å½±å“.

OBJECTIVES: To observe the effects of electroacupuncture (EA) on the phosphatidylinositol-3-kinase (PI3K)/protein kinase B (Akt)/cAMP response element binding protein (CREB) signaling pathway-related proteins and hippocampal neuron apoptosis in diabetic cognitive impairment (DCI) rats, and to explore the mechanisms of EA in treating DCI. METHODS: Adult male SD rats were randomly divided into normal, model, and EA groups, with 12 rats in each group. The animal model of DCI was replicated using a high-fat, high-sugar diet combined with low-dose streptozotocin. The EA group received EA stimulation at "Yishu" (EX-B6), "Zusanli" (ST36), "Baihui" (GV20), and "Dazhui" (GV14). Blood glucose contents of the rats in each group were measured. The Morris water maze test was used to assess the learning and memory abilities of rats. Transmission electron microscopy was used to observe the ultrastructure of hippocampal CA1 neurons. Nissl staining was used to observe the pathological changes in hippocampal CA1 neurons. TUNEL staining was used to detect the apoptosis in hippocampal CA1 neurons. Western blot was used to detect the protein expression levels of p-PI3K/PI3K and p-Akt/Akt, as well as CREB, p-CREB, cysteine aspartate pro-tease (Caspase)-3, B-cell lymphoma-2 (Bcl-2), and Bcl-2 related X protein (Bax) in the hippocampal tissue of rats. RESULTS: Compared with the normal group, the rats' random blood glucose contents were significantly increased (P<0.01), the escape latency prolonged (P<0.01), and the original platform crossing counts reduced (P<0.01) in the model group. Significant damage to hippocampal CA1 neurons, a significantly increased neuronal apoptosis index (P<0.01), decreased ratio of p-PI3K/PI3K and p-Akt/Akt and expression of CREB, p-CREB and Bcl-2 proteins, increased expression of Caspase-3 and Bax proteins (P<0.01) were observed in the hippocampal tissue of rats in the model group. Compared with the model group, the rats in the EA group showed decreased random blood glucose content (P<0.01), shortened escape latency (P<0.01), increased original platform crossing counts (P<0.01), improved quantity and pathological morphology and ultrastructure of hippocampal CA1 neurons, reduced neuronal apoptosis index (P<0.01), increased ratio of p-PI3K/PI3K and p-Akt/Akt, and expression of CREB, p-CREB and Bcl-2 proteins (P<0.05, P<0.01) in the hippocampal tissue, and decreased expression of Caspase-3 and Bax proteins (P<0.01). CONCLUSIONS: EA can improve the learning and memory abilities of rats with DCI, and the mechanism may be related to the regulation of the expression of PI3K/Akt/CREB signaling pathway-related proteins, which attenuates the neuronal apoptosis in the hippocampus of rats, and improves the neural function.

Effect of an Airbag-selective Portal Vein Blood Arrester on the Liver after Hepatectomy: A New Technique for Selective Clamping of the Portal Vein.

OBJECTIVE: A novel technique was explored using an airbag-selective portal vein blood arrester that circumvents the need for an intraoperative assessment of anatomical variations in patients with complex intrahepatic space-occupying lesions. METHODS: Rabbits undergoing hepatectomy were randomly assigned to 4 groups: intermittent portal triad clamping (PTC), intermittent portal vein clamping (PVC), intermittent portal vein blocker with an airbag-selective portal vein blood arrester (APC), and without portal blood occlusion (control). Hepatic ischemia and reperfusion injury were assessed by measuring the 7-day survival rate, blood loss, liver function, hepatic pathology, hepatic inflammatory cytokine infiltration, hepatic malondialdehyde levels, and proliferating cell nuclear antigen levels. RESULTS: Liver damage was substantially reduced in the APC and PVC groups. The APC animals exhibited transaminase levels similar to or less oxidative stress damage and inflammatory hepatocellular injury compared to those exhibited by the PVC animals. Bleeding was significantly higher in the control group than in the other groups. The APC group had less bleeding than the PVC group because of the avoidance of portal vein skeletonization during hepatectomy. Thus, more operative time was saved in the APC group than in the PVC group. Moreover, the total 7-day survival rate in the APC group was higher than that in the PTC group. CONCLUSION: Airbag-selective portal vein blood arresters may help protect against hepatic ischemia and reperfusion injury in rabbits undergoing partial hepatectomy. This technique may also help prevent liver damage in patients requiring hepatectomy.

Rosai-Dorfman Disease, Presenting as a Right Atrial Mass with Involvement of the Tricuspid Valve in a 54-Year-Old Woman.

BACKGROUND Sinus histiocytosis with massive lymphadenopathy (SHML), Rosai-Dorfman disease, or Rosai-Dorfman-Destombes disease (RDD), is a rare non-Langerhans cell of unknown etiology. This report is of a case of isolated SHML, or Rosai-Dorfman disease, presenting as a right atrial mass with involvement of the tricuspid valve in a 54-year-old woman. This case shows the challenges of diagnosing this condition in the heart and the challenges of treating this rare disease with the limited information on the efficacy of the treatment modalities. CASE REPORT A 54-year-old Asian woman presented to the Emergency Department with chest and right upper quadrant pain. Transthoracic echocardiogram and computed tomography angiography showed a right atrium mass at the level of the tricuspid valve, causing moderate-severe regurgitation. Partial tumor debulking with biopsies later showed pink-yellow soft tissue, with histopathology showing histiocytes demonstrating emperipolesis. The tumor was positive for CD68 and S100 and negative for CD1a, consistent with Rosai-Dorfman disease. Subsequently the patient received targeted therapy with cobimetinib, without worsening cardiac function or disease progression. CONCLUSIONS This case highlights the challenging histopathological diagnosis of SHML, or Rosai-Dorfman disease, particularly in non-lymphoid tissue, such as the heart. Obtaining tissue for diagnosis can be challenging in this organ. Treatment is challenging when the mass cannot be extracted completely, like in our case, because other forms of therapies are not well studied and warrant further investigation, such as cobimetinib, which is a MEK pathway inhibitor approved in 2022 by the US Food and Drug Administration for histiocytic neoplasms.