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Abstract Background Many chronic diseases, including diabetes, heart disease, cancer, and respiratory problems, can lead to emotional distress, anxiety, and depression among patients. Likewise, psychological conditions such as anxiety and depression can elevate the risk of developing chronic diseases. The objective of the study was to examine the prevalence of stress, anxiety, and depression in individuals with chronic diseases, as well as to identify the chronic disease with the highest prevalence among all chronic conditions and the factors associated with stress, anxiety, and depression. Results In our study, the prevalence rate of stress, anxiety, and depression in patients having chronic diseases was found to be 68.7%, 51.1%, and 58.8%, respectively. The chronic diseases which are included in this study are cardiovascular diseases, metabolic disorders, cancer, respiratory disorders, degenerative disorders, chronic kidney disease, and chronic liver disorders. Among these diseases, cardiovascular disease patients were found to have the highest prevalence of stress, anxiety, and depression. The psychosocial determinants that can trigger stress, anxiety, and depression were analyzed. The factors like age, marital status, primary caretakers of the patient, social isolation, length of hospital stay, social relationships, number of frequent visits to the hospital/month, and the lifestyle of the patient have a significant association with the levels of stress, anxiety, and depression. Factors like monthly income and educational status were also found to be statistically significant with the stress levels, and length of intensive care unit (ICU) stay was significantly associated with the levels of anxiety. Conclusion In conclusion, this study found a high prevalence of stress, anxiety, and depression among patients with chronic disease(s). Among all the chronic diseases, cardiovascular disease patients were found to have the highest prevalence of stress, anxiety, and depression. In addition, our study also identified several psychosocial factors that contribute to the development of these mental health conditions which exacerbate the present chronic condition of the patient. These findings highlight the importance of considering the impact of chronic disease on mental health problems.

Bone metastasis is a general complication of advanced carcinomas, usually seen in breast cancer, prostate cancer, non-small cell lung cancer and multiple myeloma. Zoledronic acid, which belongs to bisphosphonates, is indicated for bone metastasis caused due to carcinomas. This case report is about a patient with carcinoma of lung (Stage 4) with bone metastasis who has been provided with zoledronic acid as a palliative treatment. The patient was a 65-year-old male with the known case of type 2 diabetes mellitus (T2DM) and ischemic heart disease (IHD) status post (s/p) coronary artery angiography (CAG) with left ventricular ejection fraction (LVEF) 30% who was on medication. He presented with chest pain and breathlessness nine months prior and his multi-detected computed tomography (MDCT) pulmonary angiography revealed bronchogenic carcinoma. A computed tomography (CT) scan showed a metabolically active lytic lesion involving the left posterior 2nd rib and degenerative changes were noted in the spine. He has now reported upper back pain for three months localised to the left and right inferior scapular region. His pain scored a nine on the Visual Analogue Scale (VAS), and he was prescribed zoledronic acid 5mg/100ml IV infusion once in 3 weeks. On a revisit, the patient was assessed to be symptomatically better, and the pain score was lowered to 6, indicating reduced severity of discomfort. In conclusion, zoledronic acid is effective in the palliative treatment of lung cancer patients with bone metastasis.

Various types of 2D organic–inorganic perovskite solar cells have been developed and investigated due to better electron transport behavior and environmental stability. Controlling the formation of phases in the 2D perovskite films has been considered to play an important role in influencing the stability of perovskite materials and their performance in optoelectronic applications. In this work, Lewis base urea was used as an effective additive for the formation of 2D Ruddlesden—Popper (RP) perovskite (BA)2(MA)n−1PbnI3n+1 thin film with mixed phases (n = 2~4). The detailed structural morphology of the 2D perovskite thin film was investigated by in situ X-ray diffraction (XRD), grazing-incidence small-angle X-ray scattering (GISAXS) and photoluminescence mapping. The results indicated that the urea additive could facilitate the formation of 2D RP perovskite thin film with larger grain size and high crystallinity. The 2D RP perovskite thin films for solar cells exhibited a power conversion efficiency (PCE) of 7.9% under AM 1.5G illumination at 100 mW/cm2.

Pharyngitis is an inflammation of the oropharynx's mucous membranes. It is typically brought on by a bacterial illness. The outburst of latest technologies has created the need for remote care of detecting diseases like pharyngitis through images of throat taken with help of smart camera. In recent years, research has forwarded with help of deep learning in classifying pharyngitis. But deep learning models require at least one hour training and requires considerably large data set to get a good accuracy. In this paper, we focused on this time constraint and are proposing a novel approach PFDP to classify pharyngitis through detection of potential features based on doctor's perspective. We have extracted the tiny portions of image which the doctor observes them as infected and calculated frequencies of the occurrences of these portions and are given to custom made decision rules. The classification results showed significant improvement in performance in terms of time taken to reach average accuracy of 70%. It has taken only 5 minutes to extract counts of infected patterns and 1 more minute to get classification results by decision rules of if-then-else rules. We have conducted the experiment on set of 800 images. Though accuracy is lesser than that of what other works achieved but time taken to extract features is significantly lower than that of previous works. Also our approach does not require training and can be applied where scarcity of dataset exists. We assure that our approach is a new direction of research and can compete with more state of the art works in future. [ABSTRACT FROM AUTHOR]

This article, titled "Impact of Photothermal Therapy on Tumor Microenvironment and Immune cell Reprogramming," explores the potential of photothermal therapy (PTT) as a treatment for breast cancer. The study conducted PTT on a breast cancer model in mice and analyzed the immune reprogramming events in vitro and in vivo after treatment. The results showed a reduction in tumor size and a transition towards an antitumorigenic state within 24 hours. The study also found an increase in pro-inflammatory macrophages and a decrease in immunosuppressive macrophages in the tumor microenvironment after PTT treatment. These findings suggest that PTT may modulate the tumor microenvironment for an antitumor immune response and reprogram macrophages. [Extracted from the article]

The coming of the robotized millennium has brought about a period of time in which artificial intelligence (AI) has a significant impact on many facets of existence for humans, including the literary arts. This research paper explores the various ways that AI is changing the field of literature. AI has had a significant and all-encompassing impact on literature, from the development of new forms of literary expression to the improvement of conventional writing techniques. The examination of literature produced by AI takes up a large amount of the paper. It highlights noteworthy endeavors and projects that use AI to produce literary works, from poetry collections to novels in their entirety. The paper explores the distinctive features of AI-generated literature, such as its stylistic inclinations, thematic concerns, and structural patterns, through case studies of texts written by AI. It also discusses how these works have been received critically, illustrating the various viewpoints held by readers, academics, and literary critics regarding the significance and uniqueness of texts created by artificial intelligence. The collaborative potential of AI in the process of creating literature is further examined in this work. It looks at how modern poets and writers are using AI tools to improve their creative processes, from coming up with ideas and getting beyond writer's block to trying out novel narrative structures and styles. The study offers insights into the useful applications and advantages of artificial intelligence (AI) in literature through surveys and interviews with authors who have used AI into their creative processes It looks forward to more developments in AI technology and how they can transform the literary industry. It provides a nuanced view of the future of literary creativity in the robotized millennium by highlighting the opportunities and problems posed by AI in the literary arena. The research advances knowledge about AI's influence on the direction of literature by combining historical study, current case studies, and futuristic conjecture. [ABSTRACT FROM AUTHOR]