Lysosomal diseases (LDs) are a group of rare inherited disorders belonging to inborn metabolism errors. LDs are characterized by the excessive storage of undegraded substrates, most often due to the enzymatic deficiency resulting from disease-causing gene variants. LDs lead to dysregulated cellular pathways and imbalanced molecular homeostasis and can affect multiple organs and tissues. Despite being rare, LDs account for a significant incidence when considered collectively. Due to complex molecular and genetic fingerprints, considerable challenges in LD management must be overcome. Diagnosis can be significantly delayed due to the broad and nonspecific clinical manifestations and the lack of specific biomarkers. Available treatments fail to fully stop the disease progression and can alter the disease's typical phenotypes with novel manifestations. Therefore, a paradigm shift is crucial to better understand LDs and provide actionable insights. Herein, we comprehensively review the literature to demonstrate that multi-omics approaches are promising for pathophysiology elucidation, biomarker discovery, and precision therapy in LDs. We recommend adopting longitudinal study designs integrated with a multi-omics-empowered framework to facilitate mechanistic delineation, biomarker discovery, and treatment development. Relevant approaches exploring the association between LDs and common neurodegenerative disorders are also discussed, paving a potential path for improved therapeutic development and ultimately improving the patient's quality of life.

The spread of tuberculosis (TB), especially multidrug-resistant TB and extensively drug-resistant TB, has strongly motivated the research and development of new anti-TB drugs. New strategies to facilitate drug combinations, including pharmacokinetics-guided dose optimization and toxicology studies of first- and second-line anti-TB drugs have also been introduced and recommended. Liquid chromatography-mass spectrometry (LC-MS) has arguably become the gold standard in the analysis of both endo- and exo-genous compounds. This technique has been applied successfully not only for therapeutic drug monitoring (TDM) but also for pharmacometabolomics analysis. TDM improves the effectiveness of treatment, reduces adverse drug reactions, and the likelihood of drug resistance development in TB patients by determining dosage regimens that produce concentrations within the therapeutic target window. Based on TDM, the dose would be optimized individually to achieve favorable outcomes. Pharmacometabolomics is essential in generating and validating hypotheses regarding the metabolism of anti-TB drugs, aiding in the discovery of potential biomarkers for TB diagnostics, treatment monitoring, and outcome evaluation. This article highlighted the current progresses in TDM of anti-TB drugs based on LC-MS bioassay in the last two decades. Besides, we discussed the advantages and disadvantages of this technique in practical use. The pressing need for non-invasive sampling approaches and stability studies of anti-TB drugs was highlighted. Lastly, we provided perspectives on the prospects of combining LC-MS-based TDM and pharmacometabolomics with other advanced strategies (pharmacometrics, drug and vaccine developments, machine learning/artificial intelligence, among others) to encapsulate in an all-inclusive approach to improve treatment outcomes of TB patients.

Methods: Data analysis was carried out to identify the variables that had a significant impact on survival. For all patients with spinal metastasis from lung cancer who received non-surgical treatment, the Tomita score, revised Tokuhashi score, modified Bauer score, Van der Linden score, classic SORG algorithm, SORG nomogram, and NESMS were calculated. The performance of the scoring systems was assessed by using receiver operating characteristic (ROC) curves at 3 months, 6 months, and 12 months. The predictive accuracy of the scoring systems was quantified using the area under the ROC curve (AUC). Results: A total of 127 patients are included in the present study. The median survival of the population study was 5.3 months (95% confidence interval [CI], 3.7–9.6 months). Low hemoglobin was associated with shorter survival (hazard ratio [HR], 1.49; 95% CI, 1.00–2.23; p =0.049), while targeted therapy after spinal metastasis was associated with longer survival (HR, 0.34; 95% CI, 0.21–0.51; p <0.001). In the multivariate analysis, targeted therapy was independently associated with longer survival (HR, 0.3; 95% CI, 0.17–0.5; p <0.001). The AUC of the time-dependent ROC curves for the above prognostic scores revealed all of them performed poorly (AUC <0.7). Conclusions The seven scoring systems investigated are ineffective at predicting survival in patients with spinal metastasis from lung cancer who are treated non-surgically.

Background: This study was conducted on 93 volunteers with type 2 diabetes to investigate the ability of acetylated wheat starch cake containing 32.1% resistant starch to control postprandial blood glucose levels. Material and methods: The study was designed using a crossover, double-blind trial method. During each testing day, after a minimum of 12 hours of overnight fasting, each participant consumed two identical cakes containing either 80 g of acetylated wheat starch or 80 g natural wheat starch with 330ml of water within 15 minutes. Blood glucose levels were measured at baseline, 60 mins (G1), and 120 mins (G2) after ingestion. The predictive value of factors that contribute to the ability of resistant starch to control postprandial blood glucose was determined by the area under the receiver operating characteristic (ROC) curve based on the combined effect of the cake weight-to-BMI ratio (g/m²BMI) and HbA1c. Results: 60 mins and 120 mins postprandial capillary glucose levels after consuming acetylated wheat starch cake (10.4 ± 1.2 và 9.2 ± 1.2 mmol/L, respectively) were significantly lower compared with natural wheat starch cake (13.3 ± 1.8 và 11.2 ± 1.8 mmol/L, respectively) (p < 0.05). For good control of postprandial blood glucose levels, a maximum of 80 g of acetylated wheat starch can be used per serving for patients with type 2 diabetes with HbA1c ≤ 7.25 without blood glucose-lowering medication is required. Conclusion: acetylated wheat starch has better ontroled of postprandial blood glucose compared with natural wheat starch in patients with type 2 diabetes. This is very suitable in the processing of diets including resistant starch for patients with type 2 diabetes for the purpose of both supporting treatment and improving quality of life.