Chimeric Antigen Receptor T Cells Targeting CD19 and GCC in Metastatic Colorectal Cancer: A Nonrandomized Clinical Trial.

Importance: Chimeric antigen receptor (CAR) T-cell therapy (CART) has transformed the treatment landscape of hematologic cancer, but has negligible effects for adult solid cancers. In this trial, an autologous CAR T-cell product demonstrated antitumor activity in heavily pretreated patients with metastatic colorectal cancer (mCRC). Objective: To evaluate the safety and efficacy of guanylate cyclase-C (GCC19) CART in participants with metastatic colorectal cancer (mCRC). Design, Setting, and Participants: This single-arm, nonrandomized, phase 1 trial was conducted at the First Hospital of Jilin University from December 3, 2020, to April 13, 2022. Data analysis was conducted from May 2022 to April 2024. Adults with relapsed and refractory mCRC expressing GCC were treated with GCC19CART, a mixture of autologous CAR T cells transduced with lentiviral vectors expressing genes that encode either CD-19 CAR or GCC CAR. Main Outcomes and Measures: Safety and tolerability of CAR T-cell therapy targeting GCC in patients with mCRC without therapeutic options is capable of conferring a reasonable likeliness of clinical benefit. Other outcomes included objective response rate, progression-free survival, overall survival, and immune activation. Results: Of 15 patients 9 (60%) were women, and the median (range) age was 44 (33-61) years. Treatment with GCC19CART was associated with the development of cytokine release syndrome and diarrhea in most patients, all of which were self-limited and manageable. The objective response rate was 40%, with a partial response in 2 of 8 and 4 of 7 patients treated with either 1 × 106 cells/kg or 2 × 106 cells/kg. Median overall survival was 22.8 months (95% CI, 13.4-26.1) at data cutoff; the median progress-free survival was 6.0 months in the high dose level group (95% CI, 3.0 to not available). Conclusions and Relevance: The results of this nonrandomized clinical trial suggest that GCC19CART was safe and tolerable in heavily pretreated patients with mCRC and is the first CAR T-cell therapy known to produce objective clinical activity in refractory cancer. Given the paucity of effective therapeutics developed for colorectal cancer in recent decades, the observation that CD-19 CART target engagement can robustly induce GCC19CART target engagement sufficient to produce objective activity may serve as a foundation to develop effective cellular therapy in mCRC and other solid cancers. Trial Registration: Chinese Clinical Trial Registry: ChiCTR2000040645.

SelK promotes glioblastoma cell proliferation by inhibiting ß-TrCP1 mediated ubiquitin-dependent degradation of CDK4.

BACKGROUND: Glioblastoma (GB) is recognized as one of the most aggressive brain tumors, with a median survival of 14.6 months. However, there are still some patients whose survival time was greater than 3 years, and the biological reasons behind this clinical phenomenon arouse our research interests. By conducting proteomic analysis on tumor tissues obtained from GB patients who survived over 3 years compared to those who survived less than 1 year, we identified a significant upregulation of SelK in patients with shorter survival times. Therefore, we hypothesized that SelK may be an important indicator related to the occurrence and progression of GBM. METHODS: Proteomics and immunohistochemistry from GB patients were analyzed to investigate the correlation between SelK and clinical prognosis. Cellular phenotypes were evaluated by cell cycle analysis, cell viability assays, and xenograft models. Immunoblots and co-immunoprecipitation were conducted to verify SelK-mediated ubiquitin-dependent degradation of CDK4. RESULTS: SelK was found to be significantly upregulated in GB samples from short-term survivors (≤ 1 year) compared to those from long-term survivors (≥ 3 years), and its expression levels were negatively correlated with clinical prognosis. Knocking down of SelK expression reduced GB cell viability, induced G0/G1 phase arrest, and impaired the growth of transplanted glioma cells in nude mice. Down-regulation of SelK-induced ER stress leads to a reduction in the expression of SKP2 and an up-regulation of ß-TrCP1 expression. Up-regulation of ß-TrCP1, thereby accelerating the ubiquitin-dependent degradation of CDK4 and ultimately inhibiting the malignant proliferation of the GB cells. CONCLUSION: This study discovered a significant increase in SelK expression in GB patients with poor prognosis, revealing a negative correlation between SelK expression and patient outcomes. Further mechanistic investigations revealed that SelK enhances the proliferation of GB cells by targeting the endoplasmic reticulum stress/SKP2/ß-TrCP1/CDK4 axis.

Silymarin targets the FXR protein through microbial metabolite 7-keto-deoxycholic acid to treat MASLD in obese mice.

BACKGROUND: Silymarin is recognized for its excellent hepato-protective properties. Recent clinical studies have examined the effects of silymarin on metabolic dysfunction-associated steatotic liver disease (MASLD), highlighting the necessity of further exploration into optimal dosages, active components, and mechanisms of action. METHODS AND RESULTS: This study assessed the anti-inflammatory activity of the principal constituents of silymarin at the cellular level. The therapeutic effects of varying silymarin doses and components on MASLD in mouse models induced by a high-fat diet (HFD) were also examined. These findings indicate the superior efficacy of 80 mg kg-1 silymarin in mitigating liver steatosis and reducing lipid accumulation compared to 30 mg kg-1 silymarin or a combination of silybin and isosilybin A. The mechanism of silymarin involves regulating gut microbiota homeostasis and influencing the TLR4/NF-κB signalling pathway through LPS. Bile acid-targeted metabolomics analysis revealed that silymarin significantly decreases the HFD-induced increase in 7-keto-deoxycholic acid (7-KDCA). Further investigations suggested that 7-KDCA as an antagonist targeted farnesoid X receptor (FXR) and that both silybin and isosilybin A could directly interact with FXR. CONCLUSION: These findings elucidate that 80 mg kg-1 of silymarin can exert therapeutic effects on MASLD mice and offer novel insights into the mechanism of silymarin in treating MASLD. Especially, it was found that silymarin could regulate bile acid metabolism, reduce the concentration of 7-KDCA, and thus perform negative feedback regulation on FXR.

Comparative analysis of the qualities of traditional and sous-vide marinated duck drumsticks.

The sous-vide technique is increasingly used to improve the quality of poultry meat; the study aimed to compare the quality of traditional and sous-vide marinated (SVM) duck drumsticks by analyzing the sensory-related, nutritional, storage-related, and in vitro digestive-related quality of duck meat. The results showed that the sensory quality scores of color, odor, and appearance, L* and a* values of duck drumsticks in SVM group were significantly increased compared with the traditional marinated (TM) group (t-test, p < 0.05, the same below), and the b* values on the outside and inside of duck drumsticks were decreased by 22.47% and 38.04%, respectively. Compared with TM group, hardness, springiness, chewiness, adhesion, cohesion, and resilience of duck drumsticks in SVM group decreased by 43.32%, 29.52%, 65.08%, 62.35%, 20.23%, and 30.33%, respectively. The moisture content and total fat content of duck drumsticks in SVM group were significantly higher than those in TM group (p < 0.05), and the protein loss, total volatile basic nitrogen, and thiobarbituric acid reactive substances values were decreased by 61.4%, 25.86%, and 20.45%, respectively. The results of in vitro digestion experiments showed that the content of free sulfhydryl groups of duck drumsticks in SVM group was significantly increased (p < 0.05), and the contents of Schiff base and carbonyl groups were significantly decreased compared with the TM group (p < 0.05). In conclusion, the SVM technology could significantly improve the sensory-related qualities, reduce the loss of nutrients, and improve the storage-related qualities of duck drumsticks. This study provided theoretical reference for the high-value application of SVM technology in duck meat.

Based on proteomics probing into the deterioration mechanism of pork batter gel caused by different cooking temperatures.

The purpose of this experiment was to explore the influence of different cooking temperatures on the deterioration characteristics of pork batter gel by using proteomics, gel electrophoresis, size and chemical bond of aggregates. The results showed that the protein molecules of the pork batter gel was degraded during heating cooking and the protein aggregates were composed of many degraded protein fragments; compared with the control group 75 °C (0 min), the significant degradation of cytoskeleton showed at 110 °C (30 min) and 121 °C (30 min) and the significant degradation of myosin complexonly appeared at 121 °C (30 min). As the heating temperature points increased, compared with the control group 75 °C (0 min), the different temperatures could promote the separation of metal ions with proteins especially at 110 °C (30 min) and 121 °C (30 min), which could ultimately influence quality of pork batter gel by the size of particle. As the increase of heating temperature points, the recombination of aggregates composed of different proteins was not conducive to the retention of capillary water, which reduced the texture of pork batter gel. This research provided theoretical support for improving the process property of the meat products.

The improvement effect of exercise on rats with chronic stress-induced depression-like behavior: a discussion based on the kynurenine pathway.

OBJECTIVE: To observe the effects of 4 weeks of voluntary wheel running on depressive-like behavior in a rat chronic stress-induced depression model to explore the anti-depressive mechanism of exercise. METHODS: In this observational study, 36 Sprague-Dawley rats were randomly divided into control, stress model, and stress exercise groups (12 rats/group). The control group received no intervention, and the stress model and stress exercise group rats underwent chronic mild unpredictable stress and isolation. The stress exercise group rats also underwent 4 weeks of voluntary wheel running. Behavioral changes and hippocampal protein and mRNA expression levels were detected. RESULTS: Voluntary wheel running significantly increased horizontal and vertical movements, sucrose intake, and the sucrose preference percentage and reduced immobility time in the forced swimming test in depression model rats. The hippocampal tumor necrosis factor-α, interleukin (IL)-6, IL-1ß, and quinolinic acid levels were significantly decreased, while the IL-4, IL-10, and kynurenic acid levels were significantly increased. Kynurenine-3-monooxygenase and 3-hydroxyanthranilate-3, 4-dioxygenase mRNA levels were downregulated, and kynurenine aminotransferase mRNA was upregulated. CONCLUSION: Voluntary wheel running improved depressive-like behavior in depression model rats. The mechanism may be related to a kynurenine pathway metabolite level imbalance, which has neurotoxic and neuroprotective effects, caused by long-term voluntary wheel running.

PICALM::MLLT10 may indicate a new subgroup of acute leukemias with miscellaneous immunophenotype and poor initial treatment response but showing sensitivity to venetoclax.

The PICALM::MLLT10 fusion gene is a rare but recurrent event in acute leukemia (AL) associated with poor prognosis. It is still confused whether PICALM::MLLT10 can solely correspond to acute myeloid leukemia (AML) or acute lymphoblastic leukemia (ALL) or acute leukemias of ambiguous lineage (ALAL). Here, we reported a series of PICALM::MLLT10 positive AL patients with miscellaneous immunophenotype including T-ALL, ALAL, AML, and B-ALL, complex karyotype, half of extramedullary disease (EMD), frequently concomitant PHF6 mutation, and poor initial treatment response to standard chemotherapy aiming to different immunophenotype, but showing sensitivity to combining chemotherapy especially integrated with venetoclax, suggesting this fusion gene may indicate a new subgroup of AL. Eighteen PICALM::MLLT10 positive patients of 533 AL patients (18/533, 3.4%) were identified by RNA sequencing in our center. We found PICALM::MLLT10 positive AL showing miscellaneous immunophenotype, higher expression of leukemic stemness genes and lower expression of biomarkers of venetoclax resistance, more extramedullary involvement, and especially poor response to conventional induction chemotherapy, but may benefit from venetoclax as well as low-dose Ara-C, granulocyte colony-stimulating factor (G-CSF), and anthracyclines combination chemotherapy. Sequential hematopoietic stem cell transplantation (HSCT) after chemotherapy combined with venetoclax may further improve long-term survival in AL patients with complete remission (CR) even measurable residual disease (MRD) positive.

Dissecting causal relationships between immune cells, plasma metabolites, and COPD: a mediating Mendelian randomization study.

Objective: This study employed Mendelian Randomization (MR) to investigate the causal relationships among immune cells, COPD, and potential metabolic mediators. Methods: Utilizing summary data from genome-wide association studies, we analyzed 731 immune cell phenotypes, 1,400 plasma metabolites, and COPD. Bidirectional MR analysis was conducted to explore the causal links between immune cells and COPD, complemented by two-step mediation analysis and multivariable MR to identify potential mediating metabolites. Results: Causal relationships were identified between 41 immune cell phenotypes and COPD, with 6 exhibiting reverse causality. Additionally, 21 metabolites were causally related to COPD. Through two-step MR and multivariable MR analyses, 8 cell phenotypes were found to have causal relationships with COPD mediated by 8 plasma metabolites (including one unidentified), with 1-methylnicotinamide levels showing the highest mediation proportion at 26.4%. Conclusion: We have identified causal relationships between 8 immune cell phenotypes and COPD, mediated by 8 metabolites. These findings contribute to the screening of individuals at high risk for COPD and offer insights into early prevention and the precocious diagnosis of Pre-COPD.

Clothing-invariant contrastive learning for unsupervised person re-identification.

Clothing change person re-identification (CC-ReID) aims to match images of the same person wearing different clothes across diverse scenes. Leveraging biological features or clothing labels, existing CC-ReID methods have demonstrated promising performance. However, current research primarily focuses on supervised CC-ReID methods, which require a substantial number of manually annotated labels. To tackle this challenge, we propose a novel clothing-invariant contrastive learning (CICL) framework for unsupervised CC-ReID task. Firstly, to obtain clothing change positive pairs at a low computational cost, we propose a random clothing augmentation (RCA) method. RCA initially partitions clothing regions based on parsing images, then applies random augmentation to different clothing regions, ultimately generating clothing change positive pairs to facilitate clothing-invariant learning. Secondly, to generate pseudo-labels strongly correlated with identity in an unsupervised manner, we design semantic fusion clustering (SFC), which enhances identity-related information through semantic fusion. Additionally, we develop a semantic alignment contrastive loss (SAC loss) to encourages the model to learn features strongly correlated with identity and enhances the model's robustness to clothing changes. Unlike existing optimization methods that forcibly bring closer clusters with different pseudo-labels, SAC loss aligns the clustering results of real image features with those generated by SFC, forming a mutually reinforcing scheme with SFC. Experimental results on multiple CC-ReID datasets demonstrate that the proposed CICL not only outperforms existing unsupervised methods but can even achieves competitive performance with supervised CC-ReID methods. Code is made available at https://github.com/zqpang/CICL.

Drug-Target Binding Affinity Prediction in a Continuous Latent Space Using Variational Autoencoders.

Accurate prediction of Drug-Target binding Affinity (DTA) is a daunting yet pivotal task in the sphere of drug discovery. Over the years, a plethora of deep learning-based DTA models have emerged, rendering promising results in predicting the binding affinities between drugs and their target proteins. However, in contrast to the conventional approach of modeling binding affinity in vector spaces, we propose a more nuanced modeling process in a continuous space to account for the diversity of input samples. Initially, the drug is encoded using the Simplified Molecular Input Line Entry System (SMILES), while the target sequences are characterized via a pretrained language model. Subsequently, highly correlative information is extracted utilizing residual gated convolutional neural networks. In a departure from existing deep learning-based models, our model learns the hidden representations of the drugs and targets jointly. Instead of employing two vectors, our hidden representations consist of two Gaussian distributions. To validate the effectiveness of our proposal, we conducted evaluations on commonly utilized benchmark datasets. The experimental outcomes corroborated that our method surpasses the state-of-the-art vectorial representation methods in terms of performance. This approach, therefore, offers potential enhancements in the precision of DTA predictions, potentially contributing to more efficient drug discovery processes.

Effect mechanism of capsaicin and dihydrocapsaicin in chili on the oxidative stability of myoglobin in duck meat.

BACKGROUND: Myoglobin (Mb) in duck meat is commonly over-oxidized when heated at high temperatures, which may worsen the color of the meat. Enhancing the oxidative stability of Mb is essential for improving the color of duck meat. Capsaicin and dihydrocapsaicin (CA-DI) in chili exhibit antioxidant properties. This study investigated the effects of CA-DI on the structure and oxidative damage of Mb by fluorescence spectroscopy, differential scanning calorimetry analysis and particle size in duck meat during heat treatment. RESULTS: When the ratio of CA-DI to Mb was 10:1 g kg-1 and heat-treated for 36 min, oxymyoglobin significantly increased, and metmyoglobin significantly decreased compared with the control group (P < 0.05). In parallel, the carbonyl content of Mb in the CA-DI group decreased by 43.40 ± 0.10%, the sulfhydryl content increased by 188 ± 0.21%, and the free radical scavenging activity of Mb was significantly enhanced (P < 0.05). Moreover, the addition of CA-DI resulted in a significant decrease in the particle size of the Mb surface (P < 0.05). When the ratio of CA-DI to Mb was 10:1 g kg-1, CA-DI enhanced the thermal stability and significantly increased the thermal denaturation temperature of Mb. The molecular docking results indicated that hydrophobic interactions and hydrogen bonds were involved in the binding of CA-DI to Mb. CONCLUSION: CA-DI could combine with Mb and improve the oxidation stability of Mb in duck meat. This suggested that CA-DI could be a potential natural antioxidant that improves the color of meat products. © 2024 Society of Chemical Industry.

A Hierarchical Graph Neural Network Framework for Predicting Protein-Protein Interaction Modulators With Functional Group Information and Hypergraph Structure.

Accurate prediction of small molecule modulators targeting protein-protein interactions (PPIMs) remains a significant challenge in drug discovery. Existing machine learning-based models rely on manual feature engineering, which is tedious and task-specific. Recently, deep learning models based on graph neural networks have made remarkable progress in molecular representation learning. However, many graph-based approaches ignore molecular hierarchical structure modeling guided by domain knowledge. In chemistry, the functional groups of a molecule determine its interaction with specific targets. Therefore, we propose a hierarchical graph neural network framework (called HiGPPIM) for predicting PPIMs by integrating atom-level and functional group-level features of molecules. HiGPPIM constructs atom-level and functional group-level graphs based on chemical knowledge and learns graph representations using graph attention networks. Furthermore, a hypergraph attention network is designed in HiGPPIM to aggregate and transform two-level graph information. We evaluate the performance of HiGPPIM on eight PPI families and two prediction tasks, namely PPIM identification and potency prediction. Experimental results demonstrate that HiGPPIM achieves state-of-the-art performance on both tasks and that using functional group information to guide PPIM prediction is effective.

Apple E3 ligase MdPUB23 mediates ubiquitin-dependent degradation of MdABI5 to delay ABA-triggered leaf senescence.

ABSCISIC ACID-INSENSITIVE5 (ABI5) is a core regulatory factor that mediates the ABA signaling response and leaf senescence. However, the molecular mechanism underlying the synergistic regulation of leaf senescence by ABI5 with interacting partners and the homeostasis of ABI5 in the ABA signaling response remain to be further investigated. In this study, we found that the accelerated effect of MdABI5 on leaf senescence is partly dependent on MdbHLH93, an activator of leaf senescence in apple. MdABI5 directly interacted with MdbHLH93 and improved the transcriptional activation of the senescence-associated gene MdSAG18 by MdbHLH93. MdPUB23, a U-box E3 ubiquitin ligase, physically interacted with MdABI5 and delayed ABA-triggered leaf senescence. Genetic and biochemical analyses suggest that MdPUB23 inhibited MdABI5-promoted leaf premature senescence by targeting MdABI5 for ubiquitin-dependent degradation. In conclusion, our results verify that MdABI5 accelerates leaf senescence through the MdABI5-MdbHLH93-MdSAG18 regulatory module, and MdPUB23 is responsible for the dynamic regulation of ABA-triggered leaf senescence by modulating the homeostasis of MdABI5.

PPII-AEAT: Prediction of protein-protein interaction inhibitors based on autoencoders with adversarial training.

Protein-protein interactions (PPIs) have shown increasing potential as novel drug targets. The design and development of small molecule inhibitors targeting specific PPIs are crucial for the prevention and treatment of related diseases. Accordingly, effective computational methods are highly desired to meet the emerging need for the large-scale accurate prediction of PPI inhibitors. However, existing machine learning models rely heavily on the manual screening of features and lack generalizability. Here, we propose a new PPI inhibitor prediction method based on autoencoders with adversarial training (named PPII-AEAT) that can adaptively learn molecule representation to cope with different PPI targets. First, Extended-connectivity fingerprints and Mordred descriptors are employed to extract the primary features of small molecular compounds. Then, an autoencoder architecture is trained in three phases to learn high-level representations and predict inhibitory scores. We evaluate PPII-AEAT on nine PPI targets and two different tasks, including the PPI inhibitor identification task and inhibitory potency prediction task. The experimental results show that our proposed PPII-AEAT outperforms state-of-the-art methods.

Bioinformatics analysis of the prognostic role of alternative splicing data in lung adenocarcinoma.

Background: As a post-transcriptional regulatory mechanism, alternative splicing (AS) is engaged in a variety of pathophysiological processes, and it has been widely reported in connection with the occurrence, progression, metastasis, and drug resistance of cancer. However, the research on AS in lung adenocarcinoma (LUAD) is very limited. In addition, the prognostic effect of AS event (ASE) on LUAD and its related mechanism are not clear. This study aimed to explore the role and potential prognostic value of ASE in LUAD. Methods: Relevant data and ASE datasets of the sample were acquired from The Cancer Genome Atlas (TCGA) and TCGASpliceSeq databases. We constructed a new prognostic criterion based on ASEs. Then, Cox regression and least absolute shrinkage and selection operator (LASSO) regression analysis were used to construct the model. Based on this model, the risk score of each ASE was calculated, and the reliability of this model was evaluated by Kaplan-Meier survival and receiver operating characteristic (ROC) curve analyses. Finally, these results were verified on different network platforms. Results: We identified seven types of ASEs related to survival. The prognostic risk model for ASEs was established. The Kaplan-Meier curve showed that compared to the low-risk group, the overall survival (OS) rate of LUAD patients in the high-risk group was lower. ROC curve analysis showed that the prognostic risk model of LUAD patients was well predicted, and the area under the curve (AUC) also confirmed this. Conclusions: This study screened the ASE related to the prognosis of LUAD patients, and provided a theoretical basis for further study of the correlation between ASE and the prognosis of LUAD patients. It has provided new ideas for developing new biomarkers and therapeutic targets for LUAD patients.

Rational molecular design converting fascaplysin derivatives to potent broad-spectrum inhibitors against bacterial pathogens via targeting FtsZ.

The filamentous temperature-sensitive mutant Z protein (FtsZ), a key player in bacterial cell division machinery, emerges as an attractive target to tackle the plight posed by the ever growing antibiotic resistance over the world. Therefore in this regard, agents with scaffold diversities and broad-spectrum antibacterial activity against Gram-positive and Gram-negative pathogens are highly needed. In this study, a new class of marine-derived fascaplysin derivatives has been designed and synthesized by Suzuki-Miyaura cross-coupling. Some compounds exhibited potent bactericidal activities against a panel of Gram-positive (MIC = 0.024-6.25 µg/mL) and Gram-negative (MIC = 1.56-12.5 µg/mL) bacteria including methicillin-resistant S. aureus (MRSA). They exerted their effects by dual action mechanism via disrupting the integrity of the bacterial cell membrane and targeting FtsZ protein. These compounds stimulated polymerization of FtsZ monomers and bundling of the polymers, and stabilized the resulting polymer network, thus leading to the dysfunction of FtsZ in cell division. In addition, these agents showed negligible hemolytic activity and low cytotoxicity to mammalian cells. The studies on docking and molecular dynamics simulations suggest that these inhibitors bind to the hydrophilic inter-domain cleft of FtsZ protein and the insights obtained in this study would facilitate the development of potential drugs with broad-spectrum bioactivities.

Predictors of amputation in patients with diabetic foot ulcers: a multi-centre retrospective cohort study.

PURPOSE: Investigating risk factors for amputation in patients with diabetic foot ulcer (DFU) and developing a nomogram prediction model. METHODS: We gathered case data of DFU patients from five medical institutions in Anhui Province, China. Following eligibility criteria, a retrospective case-control study was performed on data from 526 patients. RESULTS: Among the 526 patients (mean age: 63.32 ± 12.14), 179 were female, and 347 were male; 264 underwent amputation. Univariate analysis identified several predictors for amputation, including Blood type-B, Ambulation, history of amputation (Hx. Of amputation), Bacterial culture-positive, Wagner grade, peripheral arterial disease (PAD), and laboratory parameters (HbA1c, Hb, CRP, ALB, FIB, PLT, Protein). In the multivariate regression, six variables emerged as independent predictors: Blood type-B (OR = 2.332, 95%CI [1.488-3.657], p < 0.001), Hx. Of amputation (2.298 [1.348-3.917], p = 0.002), Bacterial culture-positive (2.490 [1.618-3.830], p <0.001), Wagner 3 (1.787 [1.049-3.046], p = 0.033), Wagner 4-5 (4.272 [2.444-7.468], p <0.001), PAD (1.554 [1.030-2.345], p = 0.036). We developed a nomogram prediction model utilizing the aforementioned independent risk factors. The model demonstrated a favorable predictive ability for amputation risk, as evidenced by its area under the receiver operating characteristics (ROC) curve of 0.756 and the well-fitted corrected nomogram calibration curve. CONCLUSION: Our findings underscore Blood type-B, Hx. Of amputation, Bacterial culture-positive, Wagner 3-5, and PAD as independent risk factors for amputation in DFU patients. The resultant nomogram exhibits substantial accuracy in predicting amputation occurrence. Timely identification of these risk factors can reduce DFU-related amputation rates.

Transcriptome Analysis of White- and Red-Fleshed Apple Fruits Uncovered Novel Genes Related to the Regulation of Anthocyanin Biosynthesis.

The red flesh coloration of apples is a result of a biochemical pathway involved in the biosynthesis of anthocyanins and anthocyanidins. Based on apple genome analysis, a high number of regulatory genes, mainly transcription factors such as MYB, which are components of regulatory complex MYB-bHLH-WD40, and several structural genes (PAL, 4CL, CHS, CHI, F3H, DFR, ANS, UFGT) involved in anthocyanin biosynthesis, have been identified. In this study, we investigated novel genes related to the red-flesh apple phenotype. These genes could be deemed molecular markers for the early selection of new apple cultivars. Based on a comparative transcriptome analysis of apples with different fruit-flesh coloration, we successfully identified and characterized ten potential genes from the plant hormone transduction pathway of auxin (GH3); cytokinins (B-ARR); gibberellins (DELLA); abscisic acid (SnRK2 and ABF); brassinosteroids (BRI1, BZR1 and TCH4); jasmonic acid (MYC2); and salicylic acid (NPR1). An analysis of expression profiles was performed in immature and ripe fruits of red-fleshed cultivars. We have uncovered genes mediating the regulation of abscisic acid, salicylic acid, cytokinin, and jasmonic acid signaling and described their role in anthocyanin biosynthesis, accumulation, and degradation. The presented results underline the relationship between genes from the hormone signal transduction pathway and UFGT genes, which are directly responsible for anthocyanin color transformation as well as anthocyanin accumulation during apple-fruit ripening.