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Essential medicines satisfy the priority health-care needs of the population. Essential medicines policies are crucial to promoting health and achieving sustainable development. Sustainable Development Goal 3.8 specifically mentions the importance of \"access to safe, effective, quality and affordable essential medicines and vaccines for all\" as a central component of Universal Health Coverage (UHC), and Sustainable Development Goal 3.b emphasises the need to develop medicines to address persistent treatment gaps.

In the present work, hydrogen gas sensing properties of palladium-capped copper oxide (Pd/CuO) thin films have been investigated. The Pd/CuO thin films were deposited on glass substrate for different deposition times (10–30 min) using direct current magnetron sputtering. The Pd/CuO thin films were characterized by x-ray diffraction, field emission scanning electron microscopy, atomic force microscopy and x-ray photoelectron spectroscopy for their structural, morphological and compositional properties, respectively. The Pd/CuO thin film sensor deposited for 10 min presents a remarkable sensing performance with fast response/recovery time of 10 s/50 s for hydrogen gas at a concentration of (1000 ppm) and optimum operating temperature of 300°C. The sensor is observed to be highly selective towards hydrogen (H 2 ) gas compared to the other gases such as carbon monoxide (CO) and ammonia (NH 3 ). The sensor is stable under high humidity conditions (60% RH). The studied Pd/CuO thin film sensor can be used to design a simple and low-cost sensor to detect low concentrations of H 2 gas for use in hydrogen-driven industries.

Background Major Depressive Disorder (MDD) is a leading cause of global disability often treated through a trial-and-error approach, yet treatment response to antidepressants remains highly variable, with remission rates below 50% after initial treatment. Predicting treatment outcomes through machine learning (ML) models offers promise, potentially enabling more personalized and effective interventions. However, methodology heterogeneity, varied sample sizes, and lack of external validation of these models limit their clinical use. Methods A comprehensive systematic review of 30 studies employing ML models for MDD treatment response prediction was conducted. The analysis included models such as Support Vector Machines (SVM), Random Forest (RF), Ensemble Models, Deep Learning, and Graph Neural Networks. Studies were selected based on predefined inclusion and exclusion criteria. Key factors evaluated included model performance, interpretability, dataset characteristics, and external validation. Results SVM models consistently demonstrated robust predictive performance across multiple studies (AUC 0.65–0.74) using clinical and symptom data, balancing accuracy and interpretability. EEG-based ML models achieved high accuracy (up to 88%) and are emerging as scalable, cost-effective tools for outpatient monitoring. Multi-omics and neuroimaging-based models showed promise in precision psychiatry but were limited by small sample sizes and generalizability challenges. Advanced models like Deep Learning and Graph Neural Networks provided valuable research insights but remain distant from clinical application. Conclusions ML models hold significant potential in enhancing the precision of antidepressant treatment selection in MDD. SVM and EEG-based ML models currently represent the most clinically viable approaches, while multi-omics, neuroimaging, and advanced deep learning models remain research-intensive. Future efforts should prioritise large-scale validation, model interpretability, and realistic implementation strategies to bridge the gap between research and clinical practice.

Halide double perovskites of (A = Cs, B(I) = Ag, B(III) = Bi, and X = Cl, Br) have gained a lot of attention as an alternative to lead perovskites due to their similar defect tolerance, low toxicity, high stability, high absorption coefficients, long carrier diffusion lengths, and tunable bandgaps. In this study, we used a slow-cooling method to synthesize single crystals of lead-free double perovskites, specifically cesium silver bismuth bromide ( ) and cesium silver bismuth chloride ( ), and investigated the impact of halide variations on the structural, electronics, and optical properties of these materials. According to X-ray diffraction (XRD), both materials crystallize in a cubic structure. In both compounds, the and octahedra (where or Cl ) were alternately connected. X-ray photoelectron spectroscopy (XPS) provided detailed insights into the electronic structure, showing slight variations in binding energies due to halide substitution. DFT calculations confirmed the stability of the cubic structure ( ) and revealed that the materials have an indirect band gap. A detailed investigation of the optical characteristics was carried out, with a focus on essential parameters such as the dielectric function, refractive index, absorption coefficient, and optical conductivity. These findings provide important insight into how the halide composition influences the optoelectronic properties of lead-free double perovskites. This understanding opens up new opportunities for green energy and substantially supports the ongoing advancement of high-efficiency and environment-friendly photovoltaic materials.

To characterize the impact of widespread inventory management policies on stock-outs of essential drugs in Zambia's health clinics and develop related recommendations. Daily clinic storeroom stock levels of artemether-lumefantrine (AL) products in 2009-2010 were captured in 145 facilities through photography and manual transcription of paper forms, then used to determine historical stock-out levels and estimate demand patterns. Delivery lead-times and estimates of monthly facility accessibility were obtained through worker surveys. A simulation model was constructed and validated for predictive accuracy against historical stock-outs, then used to evaluate various changes potentially affecting product availability. While almost no stock-outs of AL products were observed during Q4 2009 consistent with primary analysis, up to 30% of surveyed facilities stocked out of some AL product during Q1 2010 despite ample inventory being simultaneously available at the national warehouse. Simulation experiments closely reproduced these results and linked them to the use of average past monthly issues and failure to capture lead-time variability in current inventory control policies. Several inventory policy enhancements currently recommended by USAID | DELIVER were found to have limited impact on product availability. Inventory control policies widely recommended and used for distributing medicines in sub-Saharan Africa directly account for a substantial fraction of stock-outs observed in common situations involving demand seasonality and facility access interruptions. Developing central capabilities in peripheral demand forecasting and inventory control is critical. More rigorous independent peer-reviewed research on pharmaceutical supply chain management in low-income countries is needed.

White rust disease caused by a biotrophic oomycete Albugo candida is one of the most serious impediments in realizing the production potential of Brassica juncea . Due to the obligate nature of the pathogen, R-gene-based resistance is unstable as the newer virulent races emerge quickly. For this, a deep understanding of the molecular basis of resistance is essential for developing durable resistant varieties. In this study, we selected one susceptible cultivar, ‘Pusa Jaikisan’ and its single R gene based resistant NIL, ‘Pusa Jaikisan WRR as the source of understanding the defense mechanism in B. juncea against A. candida . Comparative histochemical analysis at 12 dpi showed higher callose deposition in the resistant cultivar than in the susceptible which hints towards its possible role in defense mechanism. Based on the biochemical markers observation, total protein was found to have a negative correlation with the resistance. The antioxidant enzymes (POX, CAT, and SOD) and non-enzymatic ROS scavenging compounds such as polyphenols and proline showed a positive correlation with the white rust resistance. Polyphenol Oxidase (PPO) total chlorophyll and total carotenoids were also found to be more abundant in the ‘Pusa Jaikisan WRR’. Based on the heat map analysis, PAL was identified to be the comparatively most induced enzyme involved in the defense mechanism. The polyphenol oxidase, total chlorophyll and total carotenoids were also found to show higher activity in the ‘Pusa Jaikisan WRR ’. Furthermore, to study the defense response of ‘Pusa Jaikisan WRR ’ compared to ‘Pusa Jaikisan’ against A. candida infection, the gene expression analyses of salicylic acid (SA)-marker PR protein genes ( PR1 and PR2 ) and jasmonic acid (JA)-marker PR protein genes ( PR3 and PR12 ) were done by qRT-PCR. Based on the results, PR2 emerged as the best possible gene for defense against A. candida followed by PR1 . PR3 and PR12 also showed positive correlation with the disease resistance which may be due to the JA pathway acting complementary to the SA pathway in case of B. juncea - A. candida interaction. This provides evidence for the JA-SA hormonal crosstalk to be synergistic in case of the white rust resistance.

The present effort describes facile and environmentally benign synthesis of 4-thiazolidinone via oxidative cyclocondensation of benzyl alcohols, various substituted aromatic anilines and thioglycolic acid using a Co-Al hydrotalcite based heterogeneous catalyst (Co@HT) in methanol act as a solvent. We have synthesized three types of Co@HT with different molar ratio Co@HT-2 (1:1), Co@HT-3 (2:1), Co@HT-4 (3:1). Characterization of synthesized Co@HT catalyst using various analysis techniques such as FT-IR, powder XRD, SEM, XPS, EDS, DTG-TGA and N 2 physical adsorption. Among the synthesized hydrotalcite, Co-HT-3 exhibit admirable catalytic activity towards oxidation of benzyl alcohol followed by cyclocondensation of respective aldehydes, anilines and thioglycolic acid into the corresponding 4-thiazolidinones in methanol at 60 ο C using O 2 as a oxidant. Furthermore, after end of the reaction, the catalyst is easily recovered and eco-friendly without any considerable loss in its catalytic efficiency. Graphic Abstract

(Indian mustard) is a commercially important oil seed crop, which is highly affected by many biotic stresses. Among them, leaf blight and powdery mildew are the most devastating diseases leading to huge yield losses in around the world. In this regard, genetic engineering is a promising tool that may possibly allow us to enhance the disease resistance against these pathogens. (non-expressor of pathogen-related gene 1) is a bonafide receptor of salicylic acid (SA) which modulates multiple immune responses in plants especially activation of induced and systemic acquired resistance (SAR). Here, we report the isolation and characterization of new homolog ( ) from The phylogenetic tree constructed based on the deduced sequence of NPR1 with homologs from other species revealed that grouped together with other known proteins of Cruciferae family, and was nearest to . Furthermore, expression analysis showed that was upregulated after SA treatment and fungal infection but not by jasmonic acid or abscisic acid. To understand the defensive role of this gene, we generated transgenic lines overexpressing , and further confirmed by PCR and Southern blotting. The transgenic lines showed no phenotypic abnormalities, and constitutive expression of activates defense signaling pathways by priming the expression of antifungal genes. Moreover, transgenic lines showed enhanced resistance to and as there was delay in symptoms and reduced disease severity than non-transgenic plants. In addition, the rate of disease spreading to uninfected or distal parts was also delayed in transgenic plants thus suggesting the activation of SAR. Altogether, the present study suggests that is involved in broad spectrum of disease resistance against fungal pathogens.

ABSTRACT Background and Aims Surgical site infections (SSIs) are a significant source of morbidity and healthcare costs following open appendectomy, particularly in resource‐limited settings. While wound irrigation with antimicrobial agents has shown potential in reducing SSI rates, evidence comparing gentamicin‐saline solution with normal saline is limited. This study aimed to determine whether gentamicin‐saline irrigation reduces SSI rates compared to normal saline alone and to identify patient‐related risk factors associated with SSI development. Methods This single‐centre, single‐blinded, randomized controlled trial included 190 patients undergoing uncomplicated emergency open appendectomy between June 2022 and June 2023. Patients were randomly assigned to two groups: one receiving 160 mg gentamicin in 400 mL normal saline for wound irrigation, and the other receiving normal saline alone. The primary outcome was the incidence of SSI within 30 days. Secondary outcomes included length of hospital stay and association of SSI with risk factors such as BMI, smoking, and alcohol use. Statistical analysis was performed using SPSS v.26. Group differences were assessed using independent t‐tests and Fisher's exact or χ2 tests as appropriate. A p value < 0.05 was considered statistically significant. Results Among 190 patients (95 per group), the overall SSI rate was 15.3%, all of which were superficial. The gentamicin group had a lower SSI rate (12.6%) compared to the saline group (17.9%), but the difference was not statistically significant (p = 0.313, RR 0.66; 95% CI, 0.298–1.478). Smoking was significantly associated with SSI occurrence (p = 0.039), while BMI showed a significant association only in the gentamicin group (p = 0.008). No association was observed with alcohol use. Conclusion SSIs contribute substantially to patient complications and healthcare expenses, particularly in lower‐resource surgical settings. The reduction in SSI incidence using gentamicin‐saline was not statistically significant when compared with normal saline as compared to gentamicin‐saline irrigation did not significantly reduce SSIs compared to saline alone in uncomplicated open appendectomy. Focus should be placed on modifiable patient‐related risk factors, particularly smoking, to reduce SSI incidence in clinical practice.

Rapeseed-mustard is one of the most important oilseed crops and providing a major source of edible oil in the world besides having other economic importance like leafy vegetables, ornamentals, and hedge crops. However, the genetic diversity present in the Brassica gene pool has not been investigated in detail. To address this problem, a study was conducted on 76 genotypes of B. juncea including cultivars, exotic lines, registered genetic stocks, advanced breeding lines, and germplasm lines. The genetic diversity was analyzed with the help of 50 polymorphic SSR and EST-SSR markers. For these genotype-marker combinations, a total of 126 alleles were amplified. All the genotypes were grouped into 5 clusters based on their dissimilarity matrix. Population structure analysis grouped the genotypes in 8 clusters and various degrees of admixture was also observed. The grouping of the genotypes appears effective as per their pedigree. The marker data was found more accurate to characterize the diversity and study the population structure than the quantitative trait data. The results of the present investigation will provide useful information for the identification of important alleles for future studies and pave the way to enhance genetic gains in Indian mustard.