Sri Padmavati Mahila Visvavidyalayam

Hypertension remains the leading modifiable contributor to cardiovascular morbidity and mortality worldwide, yet blood pressure control rates remain suboptimal despite effective pharmacotherapy and lifestyle interventions. In parallel, oral diseases—particularly gingivitis and periodontitis—are highly prevalent chronic inflammatory conditions that share social and behavioural risk factors with hypertension and may also contribute to blood pressure elevation through biologically plausible pathways. Over the last decade, the oral–systemic paradigm has expanded from epidemiologic associations to mechanistic models implicating immune activation, endothelial dysfunction, oxidative stress, and microbiome-driven metabolic signalling. A distinctive and clinically relevant pathway is the enterosalivary nitrate–nitrite–nitric oxide axis, which relies on nitrate-reducing oral bacteria to support nitric oxide bioavailability and vascular homeostasis. Disruption of these bacterial communities—through antiseptic mouthwashes, dysbiosis, or periodontal inflammation—has been linked to altered nitrite generation and modest but measurable increases in blood pressure in experimental and clinical settings. In addition, high-throughput sequencing studies increasingly suggest that salivary microbiome signatures and functional potential differ between normotensive and hypertensive individuals, raising the possibility that salivary profiling may contribute to hypertension risk stratification and personalised prevention strategies. This narrative review synthesises evidence from observational studies, meta-analyses, Mendelian-randomisation-informed frameworks, interventional periodontal trials, and microbiome-focused investigations to clarify current knowledge on the oral health–microbiome–blood pressure nexus. We highlight methodological considerations in salivary microbiome research, discuss translational implications for dental and medical practice, and propose research priorities to establish causality and identify actionable interventions.

Pyrazole and phthalazine moieties receive special attention in the pharmaceutical and medical industries as essential ingredients in certain drugs. It is known that these substances exhibit a wide range of biological functions. A new method has been developed for the synthesis of pyridinefused pyrazolo[1,2-b]phthalazine derivatives via a three-component reaction of phthalhydrazide, aromatic aldehydes, and 2-aminopropene-1,1,3-tricarbonitrile. This transformation presumably occurs via Knoevenagel condensation, Michael addition, cyclization and isomerization sequence of reactions. Noteworthy features of this protocol include easy isolation, a broad substrate range, noncolumn chromatographic separation and high product yields. Benzaldehydes containing electronwithdrawing groups, such as Br, Cl, F, CN and NO<sub>2</sub>, were found to be very reactive in the process and to provide good yields of the appropriate pyridine-fused pyrazolo[1,2-b]phthalazine derivatives. In addition, the electron-donating groups such as hydroxyl, methoxy, ethoxy and isopropyl were also favourable for the transformation. In conclusion, the current study describes a straightforward new one-pot, three-component method for the synthesis of pyridine-fused pyrazolo[1,2-b]phthalazine derivatives. The transformation requires the use of an inexpensive and readily available catalyst and does not require column chromatographic purification for isolation of products. The devised protocol's primary advantages are its straightforward experimental process, wide range of substrates, and high yields.

Literature across cultures has long explored women's desire as a point of tension between personal agency and social norms. This article examines how Indu Menon's "The Lesbian Cow", Ismat Chughtai's "Lihaaf", and Charlotte Perkins Gilman's "The Yellow Wallpaper" construct the female body as a contested space through the intersection of queer desire, domestic imprisonment, and medical surveillance. Although the narratives emerge from disparate temporal and cultural contexts such as postmodern Indian healthcare, colonial Muslim aristocracy, and nineteenth-century American psychiatry- they converge in their representation of women whose emotional, sexual, and psychological needs are pathologized. Drawing on feminist and queer theoretical frameworks, this paper argues that all three protagonists resist heteropatriarchal power structures not through overt rebellion but through metaphorical self-reconstitution: the cow-woman hybrid in "The Lesbian Cow", the gloomy world of "Lihaaf", and the imagined woman trapped in "The Yellow Wallpaper." These metaphorical transformations expose how institutions-marriage, medicine, and domesticity-become technologies of discipline that attempt to normalize women's bodies and desires. Ultimately, the article contends that women's "madness", queerness, or monstrosity is not an inherent condition but a defensive space created in response to structural erasure.

During medical emergencies, quick and accurate drug recommendations are essential when doctors are not available. The proposed system is intended to develop a Drug Recommendation System (DRS) in the field of data science using machine learning techniques that can help in making faster decisions. The system processes patients' symptoms and medical history in real time using predictive analytics to provide individual medication recommendations for treating patients. This offers real-time, secure, and personalized care, improving response time and accuracy in acute situations and assessing the system's performance and user satisfaction through user feedback.

The burgeoning growth of genomic studies has likewise augmented the exposure and accessibility of marine genetic sources (MGRs), but it has also amplified the danger of misuse of the traditional knowledge (TK) of Indigenous and local peoples (ILCs). Within the new Biodiversity Beyond National Jurisdiction (BBNJ) framework, to ensure equitable access and benefit-sharing (ABS), new methods are needed to track provenance and protect community rights. This paper will describe an artificial intelligence pipeline that can be used to identify possible misappropriation of marine TK in genomic databases. Structured and unstructured data, such as public genomic repositories, biodiversity occurrence datasets, ethnobiological registries, patents, permits, and ILC consent protocols, are combined together in data integration. Preprocessing forms a provenance graph model with provenance-rich graphs between samples, sequences, publications, collectors, permits, and communities. Multimodal AI algorithms are implemented: natural language transformers categorize language used in publications related to TK, DNA sequence models detect aberrant patterns, and graph neural networks predict suspicious provenance propagation. Ensemble classifiers combine these modalities to provide risk scores, and anomaly detectors identify metadata anomalies. Cross-validation and temporal holdout evaluation has shown high performance considering high recall in legal risk detection. Its strength and ethical soundness are guaranteed by case studies, expert review, and adversarial stress tests. The framework adds a scalable, auditable marine TK protection tool and assists in meeting ABS requirements.

Aim: This study aimed to develop and validate a rapid, accurate, and stability-indicating ultra-performance liquid chromatography (UPLC) method for the simultaneous estimation of Rosuvastatin and Bempedoic acid in bulk and pharmaceutical dosage form. Materials and Methods: Chromatographic separation was achieved using an Acquity UPLC BEH C18 column (50 mm × 1.1 mm, 1.7 µm) with a mobile phase consisting of Acetonitrile: Ammonium formate pH-3.0/OPA in a ratio of 20:80 v/v, at a flow rate of 0.2 mL/min. Detection was carried out at 240 nm. The method was validated in accordance with ICH Q2(R1) guidelines for system suitability, linearity, precision, accuracy, specificity, robustness, limit of detection, and limit of quantitation. Forced degradation studies were performed under acidic, basic, oxidative, thermal, and photolytic conditions to evaluate the stability￾indicating nature of the method. Results and Discussion: Rosuvastatin and Bempedoic acid were well resolved with retention times of 0.627 and 1.254 min, respectively. The method demonstrated excellent linearity (r² > 0.999), with acceptable precision (%relative standard deviation < 2%), recovery (98–102%), and robustness. Significant degradation was observed under acid and oxidative stress, while the method successfully resolved all degradation peaks from the analytes. Conclusion: The developed UPLC method is sensitive, reliable, and stability-indicating. It is suitable for routine analysis and quality control of Rosuvastatin and Bempedoic acid in combined dosage forms

Abstract - Over the last decade, Automatic Speech Recognition (ASR)—have advanced substantially. The field has undergone a fundamental transformation with the introduction of end-to-end models, and its development has been further accelerated by recent developments in attention-based techniques and transfer learning on large- This paper compares state-of-the-art techniques in detail and provides a thorough review of research done in Hindi ASR since 2010. It examines modern methods for both monolingual and multilingual systems with an emphasis on deep learning models. This study examines multiple models on publicly available speech datasets to evaluate their performance for practical implementation. It also discusses open-source ASR research findings, challenges, and future directions, especially in mitigating data dependency, improving generalizability across low-resource languages, handling speaker variability, and operating in noisy conditions.

Objective: Tepotinib, a recent Food and Drug Administration (FDA) approved anticancer drug, currently lacks an official pharmacopeial RP-HPLC method for quantification, and its degradation kinetics remain unexplored. This study aimed to develop a rapid, robust, and eco-friendly RP-HPLC method for the quantification of tepotinib and to investigate its degradation kinetics. Methods: An Analytical Quality by Design (AQbD) approach was employed. The critical method parameters were screened using a Plackett–Burman design and further optimized through a Central Composite Design. Chromatographic separation was achieved on a SunFire C18 column (250 × 4.6 mm, 5 µm) using a methanol: 0.1% OPA (52:48, v/v) mobile phase at a flow rate of 1.0 mL/min with UV detection at 272 nm. Forced degradation studies were conducted under hydrolytic, oxidative, and thermal stress. The resulting degradation kinetics were then determined. The method was validated according to the ICH Q2(R2) guidelines. Greenness and sustainability were evaluated using various green analytical metrics and the Efficient-Valid-Green (EVG) framework. Results: The developed method achieved efficient separation of tepotinib in only five minutes with a retention time of 2.4 min. Method validation confirmed excellent linearity over 22.5–157.5 µg/ml (R² = 0.9995),%RSD for intra-and inter-day precision were 0.7 and 0.5 %, mean recovery was 99.94 %. LOD and LOQ were 0.38 µg/ml and 1.14 µg/ml, respectively. Forced degradation studies revealed significant degradation under hydrolytic, oxidative, and thermal conditions, following zero-order kinetics. The greenness assessment indicated a low ecological impact, reduced solvent consumption, and minimal waste generation. Conclusion: An AQbD-based, environmentally friendly RP-HPLC method was successfully developed and validated for quantifying tepotinib and was applied to study its degradation kinetics. This method offers environmental sustainability and is suitable for routine pharmaceutical quality control of tepotinib.