Cortisol—the most important steroid hormone with a significant effect on body metabolism—strongly affects peripheral tissues and the central nervous system. Fluctuations in cortisol secretion often accompany psychiatric disorders, and normalization of its levels correlates with improvement in the patient’s health. This indicates that cortisol may be useful as a biological marker that can help determine the likelihood of mental illness, its impending onset, and the severity of symptoms, which is especially important in the face of the increasing prevalence of mental disorders, including those associated with social isolation and anxiety during the COVID-19 pandemic. This publication reviews recent reports on cortisol levels in healthy participants and shows the current state of knowledge on changes in the levels of this hormone in people at risk for depression, bipolar disorder, and psychosis. It shows how people with psychiatric disorders react to stressful situations and how the applied therapies affect cortisol secretion. The influence of antidepressants and antipsychotics on cortisol levels in healthy people and those with mental disorders is also described. Finally, it reviews publications on the patterns of cortisol secretion in patients in remission.

Herbs used for medical purposes are required to meet high pharmacopoeial quality standards, whereas spices used as additives to dishes and food products do not have to meet such rigorous standards. Therefore, the aim of this paper was to compare medicinal herbs and spices of the same plant species that are applied in different areas with regard to the total phenolic content (TPC) and total antioxidant capacity (TAC) of their methanolic and water extracts. This study showed that the TPC values of both extracts prepared from medicinal herbs and spices as quantified using the Folin-Ciocalteu reagent did not differ significantly; however, the TAC values obtained by the DPPH assays of the methanol and water extracts differed significantly. No such differences were found for the same extracts when the FRAP assay was used for analysis. This study shows that the level of antioxidants is dependent on the plant species and the botanical family. Plants belonging to the Lamiaceae and Asteraceae families are richer in phenolic compounds and have stronger antioxidant potentials than those originating from the Apiaceae family. Multivariate statistical analysis indicates that the majority of medicinal herbs and spices of the same plant species are found in the same cluster. In addition, the extraction solvent was identified as one of the factors influencing the clustering of the plants on the PCA scatterplot and CA dendrogram.

The aim of this work was to evaluate the antioxidant potential of teas prepared from twenty-four commercially available berries and flowers of Sambucus nigra L. in relation to their phenolic profile, as reflected by the most representative phenolic acids (caffeic, chlorogenic, p-coumaric, ferulic, gallic and syringic acids); flavonols (quercetin, kaempferol, myricetin and rutin); and total phenolic (TPC), phenolic acid (TAC) and flavonoid (TFC) contents. The infusions prepared from elderflowers contained more abundant phenolic compounds than the elderberry infusions. The TPC of these infusions ranged from 19.81 to 23.90 mg of gallic acid equivalents/g dry weight of sample (GAE/g DW) for elderberries and from 15.23 to 35.57 mg GAE/g DW for elderflowers, whereas the TFC ranged from 2.60 to 4.49 mg of rutin equivalents/g dry weight of sample (RUTE/g DW) in elderberry infusions and from 5.27 to 13.19 mg RUTE/g DW in elderflower infusions. Among the phenolic compounds quantified in this study, quercetin (2.07–9.48 mg/g DW) and myricetin (1.17–9.62 mg/g DW) had the highest concentrations in the teas prepared from berries and flowers, respectively. Moreover, the antioxidant potential of elder infusions assessed by 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical and ferric reducing antioxidant power (FRAP) assays revealed that the teas prepared from flowers had higher mean DPPH and FRAP activities than the teas prepared from berries. Therefore, elder beverages could be important dietary sources of natural antioxidants that contribute to the prevention of diseases caused by oxidative stress.

In recent years, co-crystals have been the subject of increasing interest within the pharmaceutical industry because these new solid forms of active pharmaceutical ingredients have the ability to enhance the bioavailability of poorly water-soluble drugs with a low dissolution rate. For this reason, it is crucial to prepare co-crystals of benzodiazepines, i.e. psychoactive drugs with a wide range of medical applications but classified as very slightly or practically insoluble in water. Thus, the objective of this research was to show to what extent the DSC method can be used as a screening tool for detection of co-crystal formation in binary physical mixtures of drugs and co-formers. To obtain potential co-crystals, eight benzodiazepines (diazepam, temazepam, oxazepam, lormetazepam, lorazepam, clonazepam, estazolam and chlordiazepoxide) were gently mixed in an agate mortar at 1:1 molar ratios with nine co-formers—succinic, glutaric, fumaric, citric and p-aminobenzoic acids, nicotinamide, saccharin, urea and caffeine, and heated under DSC conditions. A detailed comparison of the DSC scans of mixtures against scans of both ingredients in isolation indicates the occurrence of subtle physical changes in the samples. Thus, additional endothermic or exothermic peaks due to melting or crystallisation suggested the formation of potential co-crystals. To conclude, this study confirms that the DSC method can be used as a rapid screening tool for co-crystal detection. In this case, based on the DSC scans, 15 physical mixtures of benzodiazepines (clonazepam, diazepam, lorazepam, oxazepam and temazepam) with co-formers (citric, fumaric, glutaric, p-aminobenzoic and succinic acids, nicotinamide, saccharin and urea) have been selected as potential co-crystals for further detailed study.

In recent times, there has been a growing interest in artificial neural networks, which are a rough simulation of the information processing ability of the human brain, as modern and vastly sophisticated computational techniques. This interest has also been reflected in the pharmaceutical sciences. This paper presents a review of articles on the subject of the application of neural networks as effective tools assisting the solution of various problems in science and the pharmaceutical industry, especially those characterized by multivariate and nonlinear dependencies. After a short description of theoretical background and practical basics concerning the computations performed by means of neural networks, the most important pharmaceutical applications of neural networks, with suitable references, are demonstrated. The huge role played by neural networks in pharmaceutical analysis, pharmaceutical technology, and searching for the relationships between the chemical structure and the properties of newly synthesized compounds as candidates for drugs is discussed.

Differential scanning calorimetry (DSC) is a tool particularly recommended for rapid compatibility screening between active pharmaceutical ingredients (APIs) and excipients, whereas thermogravimetric analysis (TGA), a complementary technique to DSC, is primarily used to assess the thermal stability of APIs and excipients. Both DSC and TGA data can be converted using multivariate statistical methods, which are profitable tools in the detection of compatibility between ingredients. Principal component analysis (PCA) enables identification of compatibility by grouping samples into two clusters in a PCA score plot: acetazolamide and mixture with its highest content, and optionally a 1:1 mixture form one cluster, excipient and mixture with its highest quantity, and optionally a 1:1 mixture the second. Any variation from the arrangement of samples in the abovementioned clusters indicates incompatibility. By using cluster analysis, compatibility can be determined by four clusters, the first consisting of API, the second of groups mixture at the ratio of 7:3 and the third of two mixtures at ratios of 3:7 and 1:1, with the excipient in the remaining fourth cluster. Generally, the combination of DSC and TGA techniques with advanced statistical methods is favorable for the qualitative assessment of compatibility in acetazolamide mixtures with excipients such as mannitol, meglumine, lactose, magnesium stearate, β-cyclodextrin, chitosan, methylcellulose, starch 1500 and PVP K-30. In addition, PXRD revealed that acetazolamide retains its crystalline form after mixing. Accordingly, incompatibilities in acetazolamide mixtures can be attributed to chemical reactions.