Bone-seeking aminophosphonate radiopharmaceuticals labeled with 177Lu are widely investigated for skeletal-targeted radionuclide therapy. However, direct comparative human dosimetry of 177Lu–EDTMP and 177Lu–DOTMP under harmonized computational conditions, incorporating bootstrap-based experimental uncertainty analysis, remains limited. Preclinical biodistribution data were extrapolated to humans using organ-mass scaling and processed within a unified voxel-based framework (IDAC-Dose 2.1) employing the ICRP Adult Male reference phantom and ICRP 107 decay data. Deterministic absorbed dose coefficients and organ-specific therapeutic indices were calculated for both compounds using a standardized computational workflow. Uncertainty propagation was implemented using parametric bootstrap resampling (10,000 iterations) based on the reported mean ± SD biodistribution data to quantify variability in absorbed dose estimates. Both compounds demonstrated prolonged skeletal residence times and dominant bone-surface irradiation. 177Lu–EDTMP delivered a modestly higher skeletal absorbed dose (∼15%) compared with 177Lu–DOTMP. However, substantially elevated renal and hepatic absorbed doses were observed with EDTMP (>160–200% relative increase). Therapeutic index analysis revealed comparable marrow selectivity but significantly improved kidney and liver sparing with DOTMP. Bootstrap-derived confidence intervals confirmed that inter-compound differences persisted beyond experimental variability. Under fully harmonized voxel-based computational conditions incorporating bootstrap-based experimental uncertainty analysis, 177Lu–DOTMP demonstrated skeletal targeting comparable to 177Lu–EDTMP while providing superior clearance-organ sparing. These findings highlight the value of standardized voxel-based comparative dosimetry and suggest that 177Lu–DOTMP may provide a more favorable therapeutic selectivity profile, pending clinical validation.
Desert-Gobi-Arid (DGA) zones are key regions for large-scale photovoltaic and wind-energy development and represent fragile dryland ecosystems with strong water limitation and slow ecological recovery. This paper critically reviews the ecological impacts of renewable-energy infrastructure in DGA-type landscapes, using China’s DGA bases as the main empirical context and evidence from ecologically comparable drylands for comparison. It examines how photovoltaic and wind facilities affect surface environments, ecological processes, and carbon cycling. Existing studies indicate that these facilities influence local microclimate, soil conditions, vegetation dynamics, and carbon exchange through shading, surface disturbance, airflow alteration, and hydrothermal redistribution. These impacts are site- and scale-dependent and are jointly controlled by facility layout, disturbance intensity, surface substrate, vegetation background, climate conditions, and management practices. Under low-disturbance design and effective management, they may support soil moisture retention, vegetation recovery, soil carbon accumulation, and ecosystem resilience, while higher disturbance may increase ecological risks such as water stress and habitat fragmentation. This review links direct emission reductions with indirect ecological effects and governance considerations and provides a case-based reference for assessing renewable-energy development in fragile dryland environments.
Abstract Background The rising global prevalence of type 2 diabetes mellitus (T2DM) necessitates the identification of efficient medications for its management. Curcumin (Cur), the principal curcuminoid found in turmeric, exhibits numerous beneficial effects on T2DM. The application of Cur for the treatment of T2DM presents several limitations, including inadequate penetration, decreased stability, poor solubility, and low bioavailability. Consequently, a versatile protective Cur encapsulation system is needed to address its natural instability. This study presents the application of Lycopodium clavatum sporopollenin (LCS) microcapsules, derived from natural micrometer-sized raw pollens, for Cur microencapsulation to enhance curcumin efficacy in an experimental rat model of T2DM. Results Over a 4-week treatment, the high-fat diet/Streptozotocin (HFD/STZ)-induced diabetic rats administered Cur-loaded LCS reduced FBG by 60%, decreased serum TNF-α by 20%, and increased IL-10 by 45% compared to curcumin diabetic rats. Furthermore, histological investigations of the kidney, pancreas, and liver revealed that Cur-loaded LCS ameliorated the organs' degenerative alterations in diabetic rats. Conclusion The current study demonstrates that microencapsulation of Cur within pollen-derived biomaterials facilitates Cur delivery and improves bioavailability, establishing it as a promising method for addressing complications related to T2DM. Graphical abstract
To synthesize recent advances in artificial intelligence (AI) (machine learning (ML)/deep learning (DL)) for climate science across climate modeling, extreme-weather analysis, renewable-energy optimization, emissions monitoring, and climate adaptation. Using a PRISMA-aligned protocol, we surveyed studies published between 2015 and 2025 across major scholarly databases. We extracted task definitions, datasets, model classes, evaluation metrics, baselines, validation design, uncertainty treatment, openness (code/data), and energy/CO _2 reporting. Evidence is organized by application domain and by methodological rigor, emphasizing transferability and operational relevance. Strong evidence exists for improved short- to medium-range forecasting, nowcasting, bias correction, and anomaly detection. Physics-guided and hybrid models, including PINNs and neural operators, increasingly rival operational numerical weather prediction (NWP) systems in targeted settings. However, robust external validation, out-of-distribution testing, uncertainty quantification, and transparent reporting of code and computational footprint remain inconsistent. AI enhances but does not replace physically based climate modeling. We contribute a field-level synthesis that combines PRISMA screening with a study-quality checklist to foreground evaluation rigor, reproducibility, and sustainability. Adoption of physics-guided architectures, probabilistic prediction, regime-aware validation, and carbon-aware benchmarking is essential for decision-grade climate AI.
Cisplatin is a highly effective chemotherapeutic agent used to treat various solid tumors; however, its clinical utility is limited by dose-dependent nephrotoxicity. Perampanel, an AMPA-receptor antagonist FDA-approved anti-seizure drug, has recently shown inhibitory effects on oxidative stress and inflammasome-mediated pyroptosis in neurological damage models. The current work examined the possible renoprotective benefits and clarified the underlying molecular signaling modified by perampanel in a cisplatin-renal injury model. Male Wistar rats were used to investigate the effect of perampanel (1 2 mg/kg/day, for 14 days) against renal injury induced by cisplatin (10 mg/kg, on the 9th day), followed by morphological, histopathological, immunohistochemical (IHC), and biochemical estimations. The administration of perampanel to cisplatin-injected rats maintained the kidney-to-body weight ratio and renal function in a dose-dependent manner. Besides, there was a great improvement in the histological features compared to the cisplatin group. IHC analysis revealed the efficient inhibitory impact of perampanel against cisplatin-induced upregulation of NF-κB p65, NLRP3, and caspase-1 expressions. Consequently, the activation of interleukin (IL)-18 and -1β inflammatory cytokines was interrupted, and their renal levels were not elevated. Eventually, the pyroptosis effector protein, gasdermin D (GSDMD), upregulation was impeded. Inflammasome inhibition by perampanel was accompanied by downregulation of the promoter signaling NF-κB p65/TNF-α, enhancement of sirtuin 3/FOXO3 antioxidant signaling alongside upregulated Nrf-2 mRNA expression and antioxidant proteins, as well as maintained balance of Bax/Bcl-2; pro-/anti-apoptotic; genes. Collectively, perampanel could attenuate cisplatin-induced renal injury through its inhibitory influence on NF-κB p65/TNF-α and NLRP3-mediated pyroptosis, in addition to enhancement of antioxidant defense and controlling apoptosis.
