New advances of TMEM88 in cancer initiation and progression, with special emphasis on Wnt signaling pathway.

Transmembrane protein 88 (TMEM88), a newly discovered protein localized on the cell membrane. Recent studies showed that TMEM88 was involved in the regulation of several types of cancer. TMEM88 was expressed at significantly higher levels in breast cancer (BC) cell line than in normal breast cell line with co-localized with Dishevelled (DVL) in the cytoplasm of BC cell line. TMEM88 silencing in the ovarian cancer cell line CP70 resulted in significant upregulation of Wnt downstream genes (c-Myc, cyclin-D1) and other Wnt target genes including JUN, PTIX2, CTNNB1 (ß-catenin), further supporting that TMEM88 inhibits canonical Wnt signaling pathway. Wnt signaling pathway has been known to play important roles in many diseases, especially in cancer. For instance, hepatocellular carcinoma (HCC) has become one of the most common tumors harboring mutations in the Wnt signaling pathway. As the inhibitor of Wnt signaling, TMEM88 has been considered to act as an oncogene or a tumor suppressor. Up-regulated TMEM88 or gene therapy approaches could be an effective therapeutic approach against tumor as TMEM88 inhibits Wnt signaling through direct interaction with DVL. Here, we review the current knowledge on the functional role and potential clinical application of TMEM88 in the control of various cancers. Highlights Wnt signaling displays an important role in several pathogenesis of cancer. Wnt signaling pathway is activated during cancer development. TMEM88 has an impact on cancer by inhibiting canonical Wnt signaling. We discuss the importance and new applications of TMEM88 in cancer therapy.

Machine learning is an effective method to predict the 3-month prognosis of patients with acute ischemic stroke.

Background and objectives: Upwards of 50% of acute ischemic stroke (AIS) survivors endure varying degrees of disability, with a recurrence rate of 17.7%. Thus, the prediction of outcomes in AIS may be useful for treatment decisions. This study aimed to determine the applicability of a machine learning approach for forecasting early outcomes in AIS patients. Methods: A total of 659 patients with new-onset AIS admitted to the Department of Neurology of both the First and Second Affiliated Hospitals of Bengbu Medical University from January 2020 to October 2022 included in the study. The patient' demographic information, medical history, Trial of Org 10,172 in Acute Stroke Treatment (TOAST), National Institute of Health Stroke Scale (NIHSS) and laboratory indicators at 24 h of admission data were collected. The Modified Rankine Scale (mRS) was used to assess the 3-mouth outcome of participants' prognosis. We constructed nine machine learning models based on 18 parameters and compared their accuracies for outcome variables. Results: Feature selection through the Least Absolute Shrinkage and Selection Operator cross-validation (Lasso CV) method identified the most critical predictors for early prognosis in AIS patients as white blood cell (WBC), homocysteine (HCY), D-Dimer, baseline NIHSS, fibrinogen degradation product (FDP), and glucose (GLU). Among the nine machine learning models evaluated, the Random Forest model exhibited superior performance in the test set, achieving an Area Under the Curve (AUC) of 0.852, an accuracy rate of 0.818, a sensitivity of 0.654, a specificity of 0.945, and a recall rate of 0.900. Conclusion: These findings indicate that RF models utilizing general clinical and laboratory data from the initial 24 h of admission can effectively predict the early prognosis of AIS patients.

ß2-Microglobulin is a Novel and Reliable Biomarker for Predicting Ischemic Stroke Recurrence: A Prospective Cohort Study.

Immune and inflammatory mechanisms play key roles in the development and outcome of acute ischemic stroke (AIS). ß2-Microglobulin (ß2M) is the light chain of major histocompatibility complex-1 (MHC-1), which can directly and quickly reflect the immune and inflammatory state of the body. Previous studies have shown a close relationship between ß2M and AIS, but its relationship with the recurrence of AIS has not been reported. This study attempted to explore the relationship between ß2M and the recurrence of AIS. A single-center AIS cohort involving 135 patients was followed for approximately 26-46 months. Clinical and laboratory data from the patients were collected when hospitalized. The endpoint was the occurrence of recurrent AIS after patients were discharged. Propensity score matching was used to match cohort groups. Cox regression analysis was used to predict risk factors for recurrent AIS, and receiver operating characteristic curve (ROC) analysis was used to calculate the optimal cutoff value for discriminating recurrence in patients with AIS. The rate of recurrence was 29.6% [95% CI, 21.8%-37.3%] in the follow-up group. Patients with higher levels of serum ß2M had a higher risk of AIS recurrence than patients with lower levels of ß2M (adjusted hazard ratio, 3.214 [95% CI, 1.557-6.633]; adjusted hazard ratio after matching, 5.831, [95% CI, 2.052-16.572]). A ß2M value of 2.31 mg/L was calculated by ROC analysis as the optimal cutoff value for AIS recurrence (area under the curve 0.770, [95% CI, 0.687-0.853]). As a quick responder to the body's immune and inflammatory states, ß2M may be a novel and reliable biomarker in predicting AIS recurrence.

Serum ß2-Microglobulin Is Closely Associated With the Recurrence Risk and 3-Month Outcome of Acute Ischemic Stroke.

Background and Purpose: Inflammation plays a significant role in the pathogenesis of acute ischemic stroke (AIS). The role of ß2-microglobulin (ß2M) as a potential initiator of the inflammatory response in AIS is unclear. The purpose of this study was to analyze the relationship of serum ß2M with the recurrence risk and 3-month outcome of AIS. Methods: A total of 205 patients with AIS were recruited, and their clinical and biochemical characteristics were collected. All patients were followed up for 3 months after stroke onset, and the occurrence of death or major disability at 3 months after onset was the outcome of interest in this study. We evaluated the association of serum ß2M levels with the National Institute of Health Stroke Scale (NIHSS) scores, modified Rankin Scale (mRS) scores, and Essen Stroke Risk Score (ESRS) values in patients with AIS. Then, we used receiver operating curve analysis to calculate the optimal cutoff value for discriminating outcomes in patients with AIS and a binary logistic regression model to evaluate the risk factors for a poor outcome after AIS. Results: Our results showed that serum ß2M levels were significantly and positively correlated with ESRS values (r = 0.176, P < 0.001) and mRS scores (r = 0.402, P < 0.001), but the levels of ß2M were not correlated with NIHSS scores (r = 0.080, P = 0.255) or with infarct volume (r = 0.013, P = 0.859). In a further study, we found that 121 patients (59.02%) had poor outcomes. The optimal ß2M cutoff to predict the 3-month outcome of AIS in this study was 1.865 mg/l, and ß2M was independently associated with a poor outcome at 3 months (OR = 3.325, 95% confidence interval: 1.089~10.148). Conclusions: In conclusion, we inferred that serum ß2M was positively associated with the recurrence risk and 3-month outcome of AIS, but it did not appear to be directly related to the severity of AIS or the size of the infarct at admission.

[Toxicity and oxidative stress on rats by hexachlorobenzene].

OBJECTIVE: To study the toxicity on rats by hexachlorobenzene (HCB), and to explore the role of oxidative stress in the mechanism of HCB intoxication. METHODS: SD female rats were fed on a powdered diet containing 0.25 per thousand or 2.00 per thousand HCB for 14 days. The content of malondialdehyde (MDA) and the activity of total-superoxide dismutase (T-SOD), catalase (CAT) and glutathione peroxidase (GSH-PX) in cerebral cortex, hippocampus, liver tissue and serum were determined. Eleven biochemical indicators including alkaline phosphatase (ALP) were surveyed. RESULTS: (1) MDA levels in cerebral cortex, hippocampus, liver and serum of the high dosage group rats and that in hippocampus and serum of the low dosage group were significantly higher than that of the control group. (2) The activity of T-SOD was increased in cerebral cortex and hippocampus of the rats in both groups (P < 0.01), but decreased in the serum of the high dosage group (P < 0.01). (3) The activity of CAT was also increased in the hippocampus of rats in the high dosage group. (4) In cerebral cortex and hippocampus of the rats in the high dosage group and in the hippocampus of the rats in the low dosage group, the activity of GSH-PX was significantly higher compared with the control group. However, in liver of both dosage groups, the activity of GSH-PX was decreased (P < 0.01). (5) The activity of serum alkaline phosphatase of both dosage groups was also decreased, but the contents of both serum albumin and total cholesterol were significantly higher than those of the control group (P < 0.01). CONCLUSION: HCB can induce enhanced lipid peroxidation on SD rats, and the oxidative stress plays an important role in the mechanism of neurotoxicity and hepatotoxicity.