Surgical management of adult hand macrodactyly in a 49-year-old patient: A case report.

BACKGROUND: Macrodactyly is a rare congenital malformation characterized by an increase in the size of all structures of a digit, accounting for less than 1% of all congenital upper extremity conditions. CASE SUMMARY: We report a case involving a 49-year-old woman who presented for the first time with untreated, radial-sided hand macrodactyly. We performed soft tissue debulking, amputation, median nerve neurotomy and coaptation, and carpal tunnel release. At the 6-year follow-up, no significant growth was observed in the bone or soft tissue of the affected area. CONCLUSION: Tissue overgrowth in patients with progressive macrodactyly can continue and progress excessively with age. Median nerve neurotomy and coaptation play a crucial role in preventing recurrence of the deformity.

Machine learning models to predict systemic inflammatory response syndrome after percutaneous nephrolithotomy.

OBJECTIVE: The objective of this study was to develop and evaluate the performance of machine learning models for predicting the possibility of systemic inflammatory response syndrome (SIRS) following percutaneous nephrolithotomy (PCNL). METHODS: We retrospectively reviewed the clinical data of 337 patients who received PCNL between May 2020 and June 2022. In our study, 80% of the data were used as the training set, and the remaining data were used as the testing set. Separate prediction models based on the six machine learning algorithms were created using the training set. The predictive performance of each machine learning model was determined by the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity and specificity using the testing set. We used coefficients to interpret the contribution of each variable to the predictive performance. RESULTS: Among the six machine learning algorithms, the support vector machine (SVM) delivered the best performance with accuracy of 0.868, AUC of 0.942 (95% CI 0.890-0.994) in the testing set. Further analysis using the SVM model showed that prealbumin contributed the most to the prediction of the outcome, followed by preoperative urine culture, systemic immune-inflammation (SII), neutrophil to lymphocyte ratio (NLR), staghorn stones, fibrinogen, operation time, preoperative urine white blood cell (WBC), preoperative urea nitrogen, hydronephrosis, stone burden, sex and preoperative lymphocyte count. CONCLUSION: Machine learning-based prediction models can accurately predict the possibility of SIRS after PCNL in advance by learning patient clinical data, and should be used to guide surgeons in clinical decision-making.

Role of endothelial glycocalyx in central nervous system diseases and evaluation of the targeted therapeutic strategies for its protection: a review of clinical and experimental data.

Central nervous system (CNS) diseases, such as stroke, traumatic brain injury, dementia, and demyelinating diseases, are generally characterized by high morbidity and mortality, which impose a heavy economic burden on patients and their caregivers throughout their lives as well as on public health. The occurrence and development of CNS diseases are closely associated with a series of pathophysiological changes including inflammation, blood-brain barrier disruption, and abnormal coagulation. Endothelial glycocalyx (EG) plays a key role in these changes, making it a novel intervention target for CNS diseases. Herein, we review the current understanding of the role of EG in common CNS diseases, from the perspective of individual pathways/cytokines in pathophysiological and systematic processes. Furthermore, we emphasize the recent developments in therapeutic agents targeted toward protection or restoration of EG. Some of these treatments have yielded unexpected pharmacological results, as previously unknown mechanisms underlying the degradation and destruction of EG has been brought to light. Furthermore, the anti-inflammatory, anticoagulative, and antioxidation effects of EG and its protective role exerted via the blood-brain barrier have been recognized.

Baohuoside I chemosensitises breast cancer to paclitaxel by suppressing extracellular vesicle/CXCL1 signal released from apoptotic cells.

Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype and chemotherapy is the cornerstone treatment for TNBC. Regrettably, emerging findings suggest that chemotherapy facilitates pro-metastatic changes in the tumour microenvironment. Extracellular vesicles (EVs) have been highly implicated in cancer drug resistance and metastasis. However, the effects of the EVs released from dying cancer cells on TNBC prognosis and corresponding therapeutic strategies have been poorly investigated. This study demonstrated that paclitaxel chemotherapy elicited CXCL1-enriched EVs from apoptotic TNBC cells (EV-Apo). EV-Apo promoted the chemoresistance and invasion of co-cultured TNBC cells by polarizing M2 macrophages through activating PD-L1 signalling. However, baohuoside I (BHS) remarkably sensitized the co-cultured TNBC cells to paclitaxel chemotherapy via modulating EV-Apo signalling. Mechanistically, BHS remarkably decreased C-X-C motif chemokine ligand 1 (CXCL1) cargo within EV-Apo and therefore attenuated macrophage M2 polarization by suppressing PD-L1 activation. Additionally, BHS decreased EV-Apo release by diminishing the biogenesis of intraluminal vesicles (ILVs) within multivesicular bodies (MVBs) of TNBC cells. Furthermore, BHS bound to the LEU104 residue of flotillin 2 (FLOT2) and interrupted its interaction with RAS oncogene family member 31 (RAB31), leading to the blockage of RAB31-FLOT2 complex-driven ILV biogenesis. Importantly, BHS remarkably chemosensitised paclitaxel to inhibit TNBC metastasis in vivo by suppressing EV-ApoCXCL1-induced PD-L1 activation and M2 polarization of tumour-associated macrophages (TAMs). This pioneering study sheds light on EV-ApoCXCL1 as a novel therapeutic target to chemosensitise TNBC, and presents BHS as a promising chemotherapy adjuvant to improve TNBC chemosensitivity and prognosis by disturbing EV-ApoCXCL1 biogenesis.

Multi-omics analysis of renal vein serum with Ischemia-Reperfusion injury.

BACKGROUND: Acute kidney injury (AKI) is frequently caused by renal ischemia-reperfusion injury (IRI). Identifying potential renal IRI disease biomarkers would be useful for evaluating AKI severity. OBJECTIVE: We used proteomics and metabolomics to investigate the differences in renal venous blood between ischemic and healthy kidneys in an animal model by identifying differentially expressed proteins (DEPs) and differentially expressed protein metabolites (DEMs). METHODS: Nine pairs of renal venous blood samples were collected before and at 20, 40, and 60 min post ischemia. The ischemia time of Group A, B and C was 20,40 and 60 min. The proteome and metabolome of renal venous blood were evaluated to establish the differences between renal venous blood before and after ischemia. RESULTS: We identified 79 common DEPs in all samples of Group A, 80 in Group B, and 131 in Group C. Further common DEPs among all three groups were Tyrosineprotein kinase, GPR15LG, KAZALD1, ADH1B. We also identified 81, 64, and 83 common DEMs in each group respectively, in which 30 DEMs were further common to all groups. Bioinformatic analysis of the DEPs and DEMs was conducted. CONCLUSION: This study demonstrated that different pathological processes occur during short- and long-term renal IRI. Tyrosine protein kinase, GPR15LG, Kazal-type serine peptidase inhibitor domain 1, and all-trans-retinol dehydrogenase are potential biomarkers of renal IRI.

Trends and predictors of changes in renal function after radical nephrectomy for renal tumours.

BACKGROUND: Chronic kidney disease (CKD) is a common postoperative complication in patients who undergo radical nephrectomy for renal tumours. However, the factors influencing long-term renal function require further investigation. OBJECTIVE: This study was designed to investigate the trends in renal function changes and risk factors for renal function deterioration in renal tumour patients after radical nephrectomy. METHODS: We monitored changes in renal function before and after surgery for 3 years. The progression of renal function was determined by the progression and degradation of CKD stages. Univariate and multivariate logistic regression analyses were used to analyse the causes of renal function progression. RESULTS: We analysed the data of 329 patients with renal tumours who underwent radical nephrectomies between January 2013 and December 2018. In this study, 43.7% of patients had postoperative acute kidney injury (AKI), and 48.3% had CKD at advanced stages. Further research revealed that patients' renal function stabilized 3 months after surgery. Additionally, renal function changes during these 3 months have a substantial impact on the progression of long-term renal function changes in patients. CONCLUSION: AKI may be an indicator of short-term postoperative changes in renal function. Renal function tests should be performed in patients with AKI after radical nephrectomy to monitor the progression of functional impairment, particularly within the first 3 months after radical nephrectomy.

Chemotherapy-elicited extracellular vesicle CXCL1 from dying cells promotes triple-negative breast cancer metastasis by activating TAM/PD-L1 signaling.

BACKGROUND: Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer, and chemotherapy still serves as the cornerstone treatment functioning by inducing cytotoxic cell death. Notably, emerging evidence suggests that dying cell-released signals may induce cancer progression and metastasis by modulating the surrounding microenvironment. However, the underlying molecular mechanisms and targeting strategies are yet to be explored. METHODS: Apoptotic TNBC cells induced by paclitaxel or adriamycin treatment were sorted and their released extracellular vesicles (EV-dead) were isolated from the cell supernatants. Chemokine array analysis was conducted to identify the crucial molecules in EV-dead. Zebrafish and mouse xenograft models were used to investigate the effect of EV-dead on TNBC progression in vivo. RESULTS: It was demonstrated that EV-dead were phagocytized by macrophages and induced TNBC metastasis by promoting the infiltration of immunosuppressive PD-L1+ TAMs. Chemokine array identified CXCL1 as a crucial component in EV-dead to activate TAM/PD-L1 signaling. CXCL1 knockdown in EV-dead or macrophage depletion significantly inhibited EV-dead-induced TNBC growth and metastasis. Mechanistic investigations revealed that CXCL1EV-dead enhanced TAM/PD-L1 signaling by transcriptionally activating EED-mediated PD-L1 promoter activity. More importantly, TPCA-1 (2-[(aminocarbonyl) amino]-5-(4-fluorophenyl)-3-thiophenecarboxamide) was screened as a promising inhibitor targeting CXCL1 signals in EVs to enhance paclitaxel chemosensitivity and limit TNBC metastasis without noticeable toxicities. CONCLUSIONS: Our results highlight CXCL1EV-dead as a novel dying cell-released signal and provide TPCA-1 as a targeting candidate to improve TNBC prognosis.

Manual acupuncture ameliorates inflammatory pain by upregulating adenosine A3 receptor in complete Freund's adjuvant-induced arthritis rats.

BACKGROUND: Adenosine A3 receptor (A3R) exerts analgesic, anti-inflammatory, and anti-nociceptive effects. In this study, we determined the analgesic mechanism of manual acupuncture (MA) in rats with complete Freund's adjuvant (CFA)-induced arthritis and explored whether MA ameliorates inflammation in these rats by upregulating A3R. METHODS: Sixty Sprague Dawley (SD) rats were randomly divided into the following groups: Control, CFA, CFA + MA, CFA + sham MA, CFA + MA + DMSO, CFA + MA + IB-MECA, and CFA + MA + Reversine groups. The arthritis rat model was induced by injecting CFA into the left ankle joints. Thereafter, the rats were subjected to MA (ST36 acupoint) for 3 days. The clinical indicators paw withdrawal latency (PWL), paw withdrawal threshold (PWT), and open field test (OFT) were used to determine the analgesic effect of MA. In addition, to explore the effect of A3R on inflammation after subjecting arthritis rats to MA, IB-MECA (A3R agonist) and Reversine (A3R antagonist) were injected into ST36 before MA. RESULTS: MA ameliorated the pathological symptoms of CFA-induced arthritis, including the pain indicators PWL and PWT, number of rearing, total ambulatory distance, and activity trajectory. Furthermore, after MA, the mRNA and protein expression of A3R was upregulated in CFA-induced arthritis rats. In contrast, the protein levels of TNF-α, IL-1ß, Rap1, and p-p65 were downregulated after MA. Interestingly, the A3R agonist and antagonist further downregulated and upregulated inflammatory cytokine expression, respectively, after MA. Furthermore, the A3R antagonist increased the degree of ankle swelling after MA. CONCLUSION: MA can alleviate inflammatory pain by inhibiting the NF-κB signaling pathway via upregulating A3R expression of the superficial fascia of the ST36 acupoint site in CFA-induced arthritis rats.

Integrated multi-omics reveal gut microbiota-mediated bile acid metabolism alteration regulating immunotherapy responses to anti-α4ß7-integrin in Crohn's disease.

Gut microbiota and related metabolites are both crucial factors that significantly influence how individuals with Crohn's disease respond to immunotherapy. However, little is known about the interplay among gut microbiota, metabolites, Crohn's disease, and the response to anti-α4ß7-integrin in current studies. Our research utilized 2,4,6-trinitrobenzene sulfonic acid to induce colitis based on the humanized immune system mouse model and employed a combination of whole-genome shotgun metagenomics and non-targeted metabolomics to investigate immunotherapy responses. Additionally, clinical cases with Crohn's disease initiating anti-α4ß7-integrin therapy were evaluated comprehensively. Particularly, 16S-rDNA gene high-throughput sequencing and targeted bile acid metabolomics were conducted at weeks 0, 14, and 54. We found that anti-α4ß7-integrin therapy has shown significant potential for mitigating disease phenotypes in remission-achieving colitis mice. Microbial profiles demonstrated that not only microbial composition but also microbially encoded metabolic pathways could predict immunotherapy responses. Metabonomic signatures revealed that bile acid metabolism alteration, especially elevated secondary bile acids, was a determinant of immunotherapy responses. Especially, the remission mice significantly enriched the proportion of the beneficial Lactobacillus and Clostridium genera, which were correlated with increased gastrointestinal levels of BAs involving lithocholic acid and deoxycholic acid. Moreover, most of the omics features observed in colitis mice were replicated in clinical cases. Notably, anti-α4ß7 integrin provided sustained therapeutic benefits in clinical remitters during follow-up, and long-lasting remission was linked to persistent changes in the microbial-related bile acids. In conclusion, gut microbiota-mediated bile acid metabolism alteration could play a crucial role in regulating immunotherapy responses to anti-α4ß7-integrin in Crohn's disease. Therefore, the identification of prognostic microbial signals facilitates the advancement of targeted probiotics that activate anti-inflammatory bile acid metabolic pathways, thereby improving immunotherapy responses. The integrated multi-omics established in our research provide valuable insights into potential mechanisms that impact treatment responses in complex diseases.

Computational identification of long non-coding RNAs associated with graphene therapy in glioblastoma multiforme.

Glioblastoma multiforme represents the most prevalent primary malignant brain tumour, while long non-coding RNA assumes a pivotal role in the pathogenesis and progression of glioblastoma multiforme. Nonetheless, the successful delivery of long non-coding RNA-based therapeutics to the tumour site has encountered significant obstacles attributable to inadequate biocompatibility and inefficient drug delivery systems. In this context, the use of a biofunctional surface modification of graphene oxide has emerged as a promising strategy to surmount these challenges. By changing the surface of graphene oxide, enhanced biocompatibility can be achieved, facilitating efficient transport of long non-coding RNA-based therapeutics specifically to the tumour site. This innovative approach presents the opportunity to exploit the therapeutic potential inherent in long non-coding RNA biology for treating glioblastoma multiforme patients. This study aimed to extract relevant genes from The Cancer Genome Atlas database and associate them with long non-coding RNAs to identify graphene therapy-related long non-coding RNA. We conducted a series of analyses to achieve this goal, including univariate Cox regression, least absolute shrinkage and selection operator regression and multivariate Cox regression. The resulting graphene therapy-related long non-coding RNAs were utilized to develop a risk score model. Subsequently, we conducted Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses on the identified graphene therapy-related long non-coding RNAs. Additionally, we employed the risk model to construct the tumour microenvironment model and analyse drug sensitivity. To validate our findings, we referenced the IMvigor210 immunotherapy model. Finally, we investigated differences in the tumour stemness index. Through our investigation, we identified four promising graphene therapy-related long non-coding RNAs (AC011405.1, HOXC13-AS, LINC01127 and LINC01574) that could be utilized for treating glioblastoma multiforme patients. Furthermore, we identified 16 compounds that could be utilized in graphene therapy. Our study offers novel insights into the treatment of glioblastoma multiforme, and the identified graphene therapy-related long non-coding RNAs and compounds hold promise for further research in this field. Furthermore, additional biological experiments will be essential to validate the clinical significance of our model. These experiments can help confirm the potential therapeutic value and efficacy of the identified graphene therapy-related long non-coding RNAs and compounds in treating glioblastoma multiforme.