Concurrent pelvic radiation with weekly low-dose cisplatin and gemcitabine as primary treatment of locally advanced cervical cancer: A phase II study

Purpose: This study was done to evaluate response, compliance and survival of weekly low dose cisplatin (20 mg/m2) and gemcitabine (125 mg/m2) concurrently with pelvic radiation as primary treatment of stage IIB-IIIB cervical cancer.Methods: External radiation consisted of 50 Gy/25 fractions using 6-10 MV photon followed by 600 cGy boost to parametrium if it was still felt thickened. Then, intracavitary radiotherapy to deliver 60 Gy at point A. Chemotherapy consisted of gemcitabine at a dose of 125 mg/ m2 was given by i.v infusion over 30 minutes immediately after cisplatin 20 mg/ m2 weekly for 5 weeks during EBRT. Forty–five eligible patients received the treatment protocol. Results: Toxicity was tolerable and manageable. No grade 4 toxicity while grade 3 was recorded in hematologic one only. In order of frequency; diarrhea, nausea and vomiting, and anemia (50%, 40%, 35.5%) were most common adverse events. Overall clinical response rate was 93.4% with pathological complete response of 62.2%. After median follow-up of 20 months, 2-year survival and progression-free survival rates were 90.5% and 81% respectively. Conclusion: Weekly combination of low- dose cisplatin and gemcitabine given concurrently with pelvic radiotherapy in primary treatment of locally advanced cervical cancer resulted in a high response rate with a good compliance. Further exploration is needed for the use of this approach prior to incorporating it into routine clinical care through phase III clinical trial

PHYTOCHEMICAL SCREENING AND THIN LAYER CHROMATOGRAPHIC OF PRUNUS DULCIS (ALMOND) MEDICINAL PLANT LEAVES USED IN FOLK MEDICINE FOR TREATMENT OF WOUNDS AND BURNS IN HUFASH DISTRICT AL MAHWEET GOVERNORATE–YEMEN

Objective: Prunus dulcis (Almond) belongs to the family Rosaceae and is rich in polyphenols, including hydroxybenzoic acids and aldehydes, flavonol and flavanone aglycones, and glycosides. The objective of current study was phytochemical screening of chemical constituents of Prunus dulcis extract.   Methods: In this study methanolic and aqueous extracts of one plant namely Prunus dulcis were screened for the presence of phytochemical constituents and tested for their antimicrobial and antioxidant activity. The qualitative phytochemical analysis revealed the results showed presence of alkaloids, terpenoids, glycosides, resins, saponins, tannins, flavonoids, phenols, and amino acid were present in the methanol extract, with absence of glycosides, and amino acids in the aqueous extracts in leaves plant.   Results: TLC tests conducted revealed Rf values in the leaves for alkaloids, flavonoids, tannins, phenols and saponins(0.92-0.96-0.96-0.95-0.96) respectively. The antimicrobial activity extracts against four bacterial isolates Staphylococcus aureus, Escherichia coli , Pseudomonas aeruginosa and Klebsiella sp. and a single fungal isolate Candida albicans with concentrations (0.5 mg/ml, and 1,0 mg/ml) of the extract were added to the disc and respective solvent was used as negative control. The antioxidative activity of leaf was evaluated by using 1,1-  diphenyl-2 picrylhydrazyl (DPPH), the results showed are 85.5%, lowest from standard, ascorbic acid 87.5%.   Conclusion: The present study showed that prunus dulcis are rich sources of useful secondary metabolites, suitable for use for medicinal purpose like treat wounds and burns diseases.                                      Peer Review History: Received 18 March 2019;   Revised 20 April; Accepted 5 May, Available online 15 May 2019 Academic Editor: Dr. Marwa A. A. Fayed, University of Sadat City, Egypt, [email protected] Received file:                Reviewer's Comments: Average Peer review marks at initial stage: 5.5/10 Average Peer review marks at publication stage: 8.5/10 Reviewer(s) detail: Dr. Rana Ahmed MohamedEl-Saied El-Fitiany, Ahram Canadian University, Giza, Egypt, [email protected] Dr. Mohamed Said Fathy Al-Refaey, University of Sadat City, Menofia, Egypt, [email protected]  Similar Articles: PHYTOCHEMICAL SCREENING AND IN VITRO ANTIOXIDANT AND ANTI-DIABETIC POTENTIALS OF PERSEA AMERICANA MILL. (LAURACEAE) FRUIT EXTRACT PHYTOCHEMICAL SCREENING AND IN-VITRO ANTIOXIDANT AND ANTI-INFLAMMATORY POTENTIAL EVALUATIONS OF METHANOLIC EXTRACTS OF COCOS NUCIFERA (L.) LEAVE

ANTIMICROBIAL AND ANTIOXIDANT ACTIVITY OF PSIDIUM GUAJAVA. (GUAVA) MEDICINAL PLANT LEAVES USED IN FOLK MEDICINE FOR TREATMENT OF WOUNDS AND BURNS IN HUFASH DISTRICT AL MAHWEET GOVERNORATE–YEMEN

Objective: Psidium guajava (PG) belongs to the family Myrtaceae that is believed to have active components that help to treat conditions like malaria, gastroenteritis, vomiting, diarrhea, dysentery, wounds, ulcers, toothache, coughs, sore throat, inflamed gums, and a number of other condition. The objective of current study was phytochemical screening of chemical constituents of Psidium guajava extract.Methods: In this study methanolic and aqueous extracts of one plant namely Psidium guajava, were screened for the presence of phytochemical constituents and tested for their antimicrobial and antioxidant activity.Results: TLC tests conducted revealed Rf values in the leaves for alkaloids, Flavonoids, Tannins, Phenols and Saponins(0.96-0.97-0.99-0.97-0.99) respectively. The antimicrobial activity extracts against four bacterial isolates Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa and Klebsiella sp. and a single fungal isolate Candida albicans with concentrations (0.5 mg/ml, and 1,0 mg/ml) of the extract were added to the disc and respective solvent was used as negative control. The antioxidative activity of leaf was evaluated by using 1,1- diphenyl-2 picrylhydrazyl (DPPH), the results showed are 88.4%, highest from standard, ascorbic acid 87.5%.Conclusion: The qualitative phytochemical analysis revealed the results showed presence of alkaloids, terpenoids, glycosides, resins, saponins, tannins, flavonoids, phenols, and amino acid were present in the methanol extract, with absence of glycosides, and amino acids in the aqueous extracts in leaves plant.                               Peer Review History: Received 24 March 2019;   Revised 10 April; Accepted 20 April, Available online 15 May 2019 Academic Editor:  Dr. Iman Muhammad Higazy, National Research Center, Egypt, [email protected] UJPR follows the most transparent and toughest ‘Advanced OPEN peer review’ system. The identity of the authors and, reviewers will be known to each other. This transparent process will help to eradicate any possible malicious/purposeful interference by any person (publishing staff, reviewer, editor, author, etc) during peer review. As a result of this unique system, all reviewers will get their due recognition and respect, once their names are published in the papers. We expect that, by publishing peer review reports with published papers, will be helpful to many authors for drafting their article according to the specifications. Auhors will remove any error of their article and they will improve their article(s) according to the previous reports displayed with published article(s). The main of it is ‘to improve the quality of a candidate manuscript’. Our reviewers check the ‘strength and weakness of a manuscript honestly’. There will increase in the perfection, and transparency. Received file:                Reviewer's Comments: Average Peer review marks at initial stage: 5.5/10 Average Peer review marks at publication stage: 7.5/10 Reviewer(s) detail: Ahmad Najib, Universitas Muslim Indonesia, Makassar, Indonesia, [email protected] Dr. Md. Shahidul Islam, USTC, Chittagong, Bangladesh, [email protected] Similar Articles: PHYTOCHEMICAL ANALYSIS AND ANTIMICROBIAL ACTIVITY OF COLOCASIA ESCULENTA (TARO) MEDICINAL PLANT LEAVES USED IN FOLK MEDICINE FOR TREATMENT OF WOUNDS AND BURNS IN HUFASH DISTRICT AL MAHWEET GOVERNORATE–YEME

The diagnostic accuracy of intraoperative frozen section biopsy for diagnosis of sentinel lymph node metastasis in breast cancer patients: a meta-analysis

: Sentinel lymph node (SLN) sampling is important for evaluating the nodal stage of breast cancer when the axillary nodes are clinically free of metastasis. The intraoperative frozen section (IFS) of SLN is used for lymph node assessment. This meta-analysis aims to provide evidence about the diagnostic accuracy and the applicability of IFS of SLN in breast cancer patients. Data were collected by searching PubMed, Cochrane, Scopus, and Web of Science electronic databases for trials matching our eligibility criteria. The statistical analysis included the sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and pooled studies' diagnostic odds ratio outcomes. The analyses were conducted using the Open Meta-analyst software. This meta-analysis pooled the results of 110 studies. The overall sensitivity of IFS for SLN metastasis was 74.7%; 95% CI [72.0, 77.2], P < 0.001. It was 31.4% 95% CI [25.2, 38.3], P < 0.001 for the micro-metastasis, and 90.2%; 95% CI [86.5, 93.0], P < 0.001 for the macro-metastasis. The overall specificity was 99.4%; 95% CI [99.2, 99.6], P < 0.001. The overall positive likelihood ratio was 121.4; 95% CI [87.9, 167.6], P < 0.001, and the overall negative likelihood ratio was 0.226; 95% CI [0.186, 0.274], P < 0.001. The overall diagnostic odds ratio of IFS for diagnosing SLN metastasis was 569.5; 95% CI [404.2, 802.4], P < 0.001. The intraoperative frozen section of SLN has good sensitivity for diagnosing breast cancer macro-metastasis. However, the sensitivity is low for micro-metastasis. The specificity is very satisfactory

Potential Role for a Panel of Immunohistochemical Markers in the Management of Endometrial Carcinoma

Background In order to improve the efficacy of endometrial carcinoma (EC) treatment, identifying prognostic factors for high risk patients is a high research priority. This study aimed to assess the relationships among the expression of estrogen receptors (ER), progesterone receptors (PR), human epidermal growth factor receptor 2 (HER2), Ki-67, and the different histopathological prognostic parameters in EC and to assess the value of these in the management of EC. Methods We examined 109 cases of EC. Immunohistochemistry for ER, PR, HER2, and Ki-67 were evaluated in relation to age, tumor size, International Federation of Gynecology and Obstetrics (FIGO) stage and grade, depth of infiltration, cervical and ovarian involvement, lymphovascular space invasion (LVSI), and lymph node (LN) metastasis. Results The mean age of patients in this study was 59.8 ± 8.2 years. Low ER and PR expression scores and high Ki-67 expression showed highly significant associations with non-endometrioid histology (p = .007, p < .001, and p < .001, respectively) and poor differentiation (p = .007, p < .001, and p <. 001, respectively). Low PR score showed a significant association with advanced stage (p = .009). Low ER score was highly associated with LVSI (p = .006), and low PR scores were associated significantly with LN metastasis (p = .026). HER2 expression was significantly related to advanced stages (p = .04), increased depth of infiltration (p = .02), LVSI (p = .017), ovarian involvement (p = .038), and LN metastasis (p = .038). There was a close relationship between HER2 expression and uterine cervical involvement (p = .009). Higher Ki-67 values were associated with LN involvement (p = .012). Conclusions The over-expression of HER2 and Ki-67 and low expression of ER and PR indicate a more malignant EC behavior. An immunohistochemical panel for the identification of high risk tumors can contribute significantly to prognostic assessments

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14

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

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

Background Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.Methods A multimethods analysis was performed as part of the GlobalSurg 3 study-a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.Findings Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3.85 [95% CI 2.58-5.75]; p&lt;0.0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63.0% vs 82.7%; OR 0.35 [0.23-0.53]; p&lt;0.0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.Interpretation Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised

Federated Learning Enables Big Data for Rare Cancer Boundary Detection

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing