Nutraceutical Analysis of Marticaria recutita (Chamomile) Dried Leaves and Flower Powder and Comparison between Them

Chamomile is known as German Chamomile (Marticaria recutita) and Roman Chamomile (Chamaemelum nobile) a very famous daisy plant. The work mainly focuses on the nutraceuticals potential of Chamomile leaf and flower of this plant. The nutrient contains of the leaf and flower power was determined by various methods. The phytochemicals screening of the leaf and flower aqueous extract was performed by the different procedure. Leaf of this plant is rich in carbohydrate, protein, fat and also rich in vitamin C, iron, zinc and calcium. Whereas flower is rich in moisture and fiber as compared to leaf. The aqueous extract of leaf of Chamomile showed the presence of steroids, terpenoids, flavonoids, tannins and saponins and flower were lacked in alkaloids, saponins, gelatin and phenolic compounds. The results record that leaf and flowers powder contains different types of nutrients and phytochmicals in it. Chamomile is rich in different bioactive compounds, antioxidant and phytochemicals; carries many pharmacological and traditional properties. Leaves, flowers and stems of Chamomile are used as anti-oxidant, analgesic, anti-viral, anti-inflammatory, anti-septic, anti-diabetic, anti-proliferative, anti-bacterial activities and many more diseases. This paper put a light on nutrient content and phytochemical properties of Chamomile leaf and flower

Quantum spin liquids on the diamond lattice

We perform a projective symmetry group classification of spin $S=1/2$ symmetric quantum spin liquids with different gauge groups on the diamond lattice. Employing the Abrikosov fermion representation, we obtain $8$ $SU(2)$, $62$ $U(1)$ and $80$ $\mathbb{Z}_{2}$ algebraic PSGs. Constraining these solutions to mean-field parton Ans\"atze with short-range amplitudes, the classification reduces to only $2$ $SU(2)$, $7$ $U(1)$ and $8$ $\mathbb{Z}_{2}$ distinctly realizable phases. We obtain both the singlet and triplet fields for all Ans\"atze, discuss the spinon dispersions, and present the dynamical spin structure factors within a self-consistent treatment of the Heisenberg Hamiltonian with up to third-nearest neighbor couplings. Interestingly, we find that a zero-flux $SU(2)$ state and some descendent $U(1)$ and $\mathbb{Z}_{2}$ states host robust gapless nodal loops in their dispersion spectrum, owing their stability at the mean-field level to the projective implementation of rotoinversion and screw symmetries. A nontrivial connection is drawn between one of our $U(1)$ spinon Hamiltonians (belonging to the nonprojective class) and the Fu-Kane-Mele model for a three-dimensional topological insulator on the diamond lattice. We show that Gutzwiller projection of the 0- and $\pi$-flux $SU(2)$ spin liquids generates long-range N\'eel order.Comment: Editors' Suggestion. 36 pages, 9 figures, 9 table

Emerging Roles and Potential Applications of Non-Coding RNAs in Cervical Cancer

Cervical cancer (CC) is a preventable disease using proven interventions, specifically prophylactic vaccination, pervasive disease screening, and treatment, but it is still the most frequently diagnosed cancer in women worldwide. Patients with advanced or metastatic CC have a very dismal prognosis and current therapeutic options are very limited. Therefore, understanding the mechanism of metastasis and discovering new therapeutic targets are crucial. New sequencing tools have given a full visualization of the human transcriptome’s composition. Non-coding RNAs (NcRNAs) perform various functions in transcriptional, translational, and post-translational processes through their interactions with proteins, RNA, and even DNA. It has been suggested that ncRNAs act as key regulators of a variety of biological processes, with their expression being tightly controlled under physiological settings. In recent years, and notably in the past decade, significant effort has been made to examine the role of ncRNAs in a variety of human diseases, including cancer. Therefore, shedding light on the functions of ncRNA will aid in our better understanding of CC. In this review, we summarize the emerging roles of ncRNAs in progression, metastasis, therapeutics, chemoresistance, human papillomavirus (HPV) regulation, metabolic reprogramming, diagnosis, and as a prognostic biomarker of CC.We also discussed the role of ncRNA in the tumor microenvironment and tumor immunology, including cancer stem cells (CSCs) in CC.We also address contemporary technologies such as antisense oligonucleotides, CRISPR–Cas9, and exosomes, as well as their potential applications in targeting ncRNAs to manage CC

Pinwheel valence bond crystal ground state of the spin-1/ 2 Heisenberg antiferromagnet on the shuriken lattice

We investigate the nature of the ground state of the spin-12 Heisenberg antiferromagnet on the shuriken lattice by complementary state-of-the-art numerical techniques, such as variational Monte Carlo (VMC) with versatile Gutzwiller-projected Jastrow wave functions, unconstrained multivariable variational Monte Carlo (mVMC), and pseudofermion/pseudo-Majorana functional renormalization group (PFFRG/PMFRG) methods. We establish the presence of a quantum paramagnetic ground state and investigate its nature, by classifying symmetric and chiral quantum spin liquids, and inspecting their instabilities towards competing valence bond crystal (VBC) orders. Our VMC analysis reveals that a VBC with a pinwheel structure emerges as the lowest-energy variational ground state, and it is obtained as an instability of the U(1) Dirac spin liquid. Analogous conclusions are drawn from mVMC calculations employing accurate BCS pairing states supplemented by symmetry projectors, which confirm the presence of pinwheel VBC order by a thorough analysis of dimer-dimer correlation functions. Our work highlights the nontrivial role of quantum fluctuations via the Gutzwiller projector in resolving the subtle interplay between competing orders

Multiomics Characterization of Preterm Birth in Low- and Middle-Income Countries.

Importance: Worldwide, preterm birth (PTB) is the single largest cause of deaths in the perinatal and neonatal period and is associated with increased morbidity in young children. The cause of PTB is multifactorial, and the development of generalizable biological models may enable early detection and guide therapeutic studies. Objective: To investigate the ability of transcriptomics and proteomics profiling of plasma and metabolomics analysis of urine to identify early biological measurements associated with PTB. Design, Setting, and Participants: This diagnostic/prognostic study analyzed plasma and urine samples collected from May 2014 to June 2017 from pregnant women in 5 biorepository cohorts in low- and middle-income countries (LMICs; ie, Matlab, Bangladesh; Lusaka, Zambia; Sylhet, Bangladesh; Karachi, Pakistan; and Pemba, Tanzania). These cohorts were established to study maternal and fetal outcomes and were supported by the Alliance for Maternal and Newborn Health Improvement and the Global Alliance to Prevent Prematurity and Stillbirth biorepositories. Data were analyzed from December 2018 to July 2019. Exposures: Blood and urine specimens that were collected early during pregnancy (median sampling time of 13.6 weeks of gestation, according to ultrasonography) were processed, stored, and shipped to the laboratories under uniform protocols. Plasma samples were assayed for targeted measurement of proteins and untargeted cell-free ribonucleic acid profiling; urine samples were assayed for metabolites. Main Outcomes and Measures: The PTB phenotype was defined as the delivery of a live infant before completing 37 weeks of gestation. Results: Of the 81 pregnant women included in this study, 39 had PTBs (48.1%) and 42 had term pregnancies (51.9%) (mean [SD] age of 24.8 [5.3] years). Univariate analysis demonstrated functional biological differences across the 5 cohorts. A cohort-adjusted machine learning algorithm was applied to each biological data set, and then a higher-level machine learning modeling combined the results into a final integrative model. The integrated model was more accurate, with an area under the receiver operating characteristic curve (AUROC) of 0.83 (95% CI, 0.72-0.91) compared with the models derived for each independent biological modality (transcriptomics AUROC, 0.73 [95% CI, 0.61-0.83]; metabolomics AUROC, 0.59 [95% CI, 0.47-0.72]; and proteomics AUROC, 0.75 [95% CI, 0.64-0.85]). Primary features associated with PTB included an inflammatory module as well as a metabolomic module measured in urine associated with the glutamine and glutamate metabolism and valine, leucine, and isoleucine biosynthesis pathways. Conclusions and Relevance: This study found that, in LMICs and high PTB settings, major biological adaptations during term pregnancy follow a generalizable model and the predictive accuracy for PTB was augmented by combining various omics data sets, suggesting that PTB is a condition that manifests within multiple biological systems. These data sets, with machine learning partnerships, may be a key step in developing valuable predictive tests and intervention candidates for preventing PTB

Prediction of gestational age using urinary metabolites in term and preterm pregnancies.

Assessment of gestational age (GA) is key to provide optimal care during pregnancy. However, its accurate determination remains challenging in low- and middle-income countries, where access to obstetric ultrasound is limited. Hence, there is an urgent need to develop clinical approaches that allow accurate and inexpensive estimations of GA. We investigated the ability of urinary metabolites to predict GA at time of collection in a diverse multi-site cohort of healthy and pathological pregnancies (n = 99) using a broad-spectrum liquid chromatography coupled with mass spectrometry (LC-MS) platform. Our approach detected a myriad of steroid hormones and their derivatives including estrogens, progesterones, corticosteroids, and androgens which were associated with pregnancy progression. We developed a restricted model that predicted GA with high accuracy using three metabolites (rho = 0.87, RMSE = 1.58 weeks) that was validated in an independent cohort (n = 20). The predictions were more robust in pregnancies that went to term in comparison to pregnancies that ended prematurely. Overall, we demonstrated the feasibility of implementing urine metabolomics analysis in large-scale multi-site studies and report a predictive model of GA with a potential clinical value

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P &lt; 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

A Novel Promising Strain of Trichoderma evansii (WF-3) for Extracellular -Galactosidase Production by Utilizing Different Carbon Sources under Optimized Culture Conditions

A potential fungal strain of Trichoderma sp. (WF-3) was isolated and selected for the production of -galactosidase. Optimum conditions for mycelial growth and enzyme induction were determined. Basal media selected for the growth of fungal isolate containing different carbon sources like guar gum (GG), soya bean meal (SM), and wheat straw (WS) and combinations of these carbon substrates with basic sugars like galactose and sucrose were used to monitor their effects on -galactosidase production. The results of this study indicated that galactose and sucrose enhanced the enzyme activity in guar gum (GG) and wheat straw (WS). Maximum -galactosidase production (213.63 UmL −1 ) was obtained when the basic medium containing GG is supplemented with galactose (5 mg/mL). However, the presence of galactose and sucrose alone in the growth media shows no effect. Soya meal alone was able to support T. evansii to produce maximum enzyme activity (170.36 UmL −1 ). The incubation time, temperature, and pH for the maximum enzyme synthesis were found to be 120 h (5 days), 28 ∘ C, and 4.5-5.5, respectively. All the carbon sources tested exhibited maximum enzyme production at 10 mg/mL concentration. Among the metal ions tested, Hg was found to be the strongest inhibitor of the enzyme. Among the chelators, EDTA acted as stronger inhibitor than succinic acid

A Novel Promising Strain of Trichoderma evansii (WF-3) for Extracellular α-Galactosidase Production by Utilizing Different Carbon Sources under Optimized Culture Conditions

A potential fungal strain of Trichoderma sp. (WF-3) was isolated and selected for the production of α-galactosidase. Optimum conditions for mycelial growth and enzyme induction were determined. Basal media selected for the growth of fungal isolate containing different carbon sources like guar gum (GG), soya bean meal (SM), and wheat straw (WS) and combinations of these carbon substrates with basic sugars like galactose and sucrose were used to monitor their effects on α-galactosidase production. The results of this study indicated that galactose and sucrose enhanced the enzyme activity in guar gum (GG) and wheat straw (WS). Maximum α-galactosidase production (213.63 UmL−1) was obtained when the basic medium containing GG is supplemented with galactose (5 mg/mL). However, the presence of galactose and sucrose alone in the growth media shows no effect. Soya meal alone was able to support T. evansii to produce maximum enzyme activity (170.36 UmL−1). The incubation time, temperature, and pH for the maximum enzyme synthesis were found to be 120 h (5 days), 28°C, and 4.5–5.5, respectively. All the carbon sources tested exhibited maximum enzyme production at 10 mg/mL concentration. Among the metal ions tested, Hg was found to be the strongest inhibitor of the enzyme. Among the chelators, EDTA acted as stronger inhibitor than succinic acid