Endogenous p53 inhibitor TIRR dissociates systemic metabolic health from oncogenic activity.

It is unclear whether metabolic health corresponds to reduced oncogenesis or vice versa. We study Tudor-interacting repair regulator (TIRR), an inhibitor of p53 binding protein 1 (53BP1)-mediated p53 activation, and the physiological consequences of enhancing tumor suppressor activity. Deleting TIRR selectively activates p53, significantly protecting against cancer but leading to a systemic metabolic imbalance in mice. TIRR-deficient mice are overweight and insulin resistant, even under normal chow diet. Similarly, reduced TIRR expression in human adipose tissue correlates with higher BMI and insulin resistance. Despite the metabolic challenges, TIRR loss improves p53 heterozygous (p53HET) mouse survival and correlates with enhanced progression-free survival in patients with various p53HET carcinomas. Finally, TIRR's oncoprotective and metabolic effects are dependent on p53 and lost upon p53 deletion in TIRR-deficient mice, with glucose homeostasis and orexigenesis being primarily regulated by TIRR expression in the adipose tissue and the CNS, respectively, as evidenced by tissue-specific models. In summary, TIRR deletion provides a paradigm of metabolic deregulation accompanied by reduced oncogenesis.

'Nowhere and no one is safe': spatial analysis of damage to critical civilian infrastructure in the Gaza Strip during the first phase of the Israeli military campaign, 7 October to 22 November 2023.

BACKGROUND: Since the Hamas attacks in Israel on 7 October 2023, the Israeli military has launched an assault in the Gaza Strip, which included over 12,000 targets struck and over 25,000 tons of incendiary munitions used by 2 November 2023. The objectives of this study include: (1) the descriptive and inferential spatial analysis of damage to critical civilian infrastructure (health, education, and water facilities) across the Gaza Strip during the first phase of the military campaign, defined as 7 October to 22 November 2023 and (2) the analysis of damage clustering around critical civilian infrastructure to explore broader questions about Israel's adherence to International Humanitarian Law (IHL). METHODS: We applied multi-temporal coherent change detection on Copernicus Sentinel 1-A Synthetic Aperture Radar (SAR) imagery to detect signals indicative of damage to the built environment through 22 November 2023. Specific locations of health, education, and water facilities were delineated using open-source building footprint and cross-checked with geocoded data from OCHA, OpenStreetMap, and Humanitarian OpenStreetMap Team. We then assessed the retrieval of damage at and with close proximity to sites of health, education, and water infrastructure in addition to designated evacuation corridors and civilian protection zones. The Global Moran's I autocorrelation inference statistic was used to determine whether health, education, and water facility infrastructure damage was spatially random or clustered. RESULTS: During the period under investigation, in the entire Gaza Strip, 60.8% (n = 59) of health, 68.2% (n = 324) of education, and 42.1% (n = 64) of water facilities sustained infrastructure damage. Furthermore, 35.1% (n = 34) of health, 40.2% (n = 191) of education, and 36.8% (n = 56) of water facilities were functionally destroyed. Applying the Global Moran's I spatial inference statistic to facilities demonstrated a high degree of damage clustering for all three types of critical civilian infrastructure, with Z-scores indicating < 1% likelihood of cluster damage occurring by random chance. CONCLUSION: Spatial statistical analysis suggests widespread damage to critical civilian infrastructure that should have been provided protection under IHL. These findings raise serious allegations about the violation of IHL, especially in light of Israeli officials' statements explicitly inciting violence and displacement and multiple widely reported acts of collective punishment.

Clearance of p16Ink4a-positive cells in a mouse transgenic model does not change ß-cell mass and has limited effects on their proliferative capacity.

Type 2 diabetes is partly characterized by decreased ß-cell mass and function which have been linked to cellular senescence. Despite a low basal proliferative rate of adult ß-cells, they can respond to growth stimuli, but this proliferative capacity decreases with age and correlates with increased expression of senescence effector, p16Ink4a. We hypothesized that selective deletion of p16Ink4a-positive cells would enhance the proliferative capacity of the remaining ß-cells due to the elimination of the local senescence-associated secretory phenotype (SASP). We aimed to investigate the effects of p16Ink4a-positive cell removal on the mass and proliferative capacity of remaining ß-cells using INK-ATTAC mice as a transgenic model of senolysis. Clearance of p16Ink4a positive subpopulation was tested in mice of different ages, males and females, and with two different insulin resistance models: high-fat diet (HFD) and insulin receptor antagonist (S961). Clearance of p16Ink4a-positive cells did not affect the overall ß-cell mass. ß-cell proliferative capacity negatively correlated with cellular senescence load and clearance of p16Ink4a positive cells in 1-year-old HFD mice improved ß-cell function and increased proliferative capacity in a subset of animals. Single-cell sequencing revealed that the targeted p16Ink4a subpopulation of ß-cells is non-proliferative and non-SASP producing whereas additional senescent subpopulations remained contributing to continued local SASP secretion. In conclusion, deletion of p16Ink4a cells did not negatively impact beta-cell mass and blood glucose under basal and HFD conditions and proliferation was restored in a subset of HFD mice opening further therapeutic targets in the treatment of diabetes.

Diabetes mellitus correlates with increased biological age as indicated by clinical biomarkers.

Chronological age (CA) is determined by time of birth, whereas biological age (BA) is based on changes on a cellular level and strongly correlates with morbidity, mortality, and longevity. Type 2 diabetes (T2D) associates with increased morbidity and mortality; thus, we hypothesized that BA would be increased and calculated it from biomarkers collected at routine clinical visits. Deidentified data was obtained from three cohorts of patients (20-80 years old)-T2D, type 1 diabetes (T1D), and prediabetes-and compared to gender- and age-matched non-diabetics. Eight clinical biomarkers that correlated with CA in people without diabetes were used to calculate BA using the Klemera and Doubal method 1 (KDM1) and multiple linear regression (MLR). The phenotypic age (PhAge) formula was used with its predetermined biomarkers. BA of people with T2D was, on average, 12.02 years higher than people without diabetes (p < 0.0001), while BA in T1D was 16.32 years higher (p < 0.0001). Results were corroborated using MLR and PhAge. The biomarkers with the strongest correlation to increased BA in T2D using KDM were A1c (R2 = 0.23, p < 0.0001) and systolic blood pressure (R2 = 0.21, p < 0.0001). BMI had a positive correlation to BA in non-diabetes subjects but disappeared in those with diabetes. Mortality data using the ACCORD trial was used to validate our results and showed a significant correlation between higher BA and decreased survival. In conclusion, BA is increased in people with diabetes, irrespective of pathophysiology, and to a lesser extent in prediabetes.