Federated Learning Approach for Secured Medical Recommendation in Internet of Medical Things Using Homomorphic Encryption.

The concept of Federated Learning (FL) is a distributed-based machine learning (ML) approach that trains its model using edge devices. Its focus is on maintaining privacy by transmitting gradient updates along with users' learning parameters to the global server in the process of training as well as preserving the integrity of data on the user-end of internet of medical things (IoMT) devices. Instead of a direct use of user data, the training which is performed on the global server is done on the parameters while the model modification is performed locally on IoMT devices. But the major drawback of this federated learning approach is its inability to preserve user privacy complete thereby resulting in gradients leakage. Thus, this study first presents a summary of the process of learning and further proposes a new approach for federated medical recommender system which employs the use of homomorphic cryptography to ensure a more privacy-preservation of user gradients during recommendations. The experimental results indicate an insignificant decrease with respect to the metrics of accuracy, however, a greater percentage of user-privacy is achieved. Further analysis also shows that performing computations on encrypted gradients at the global server scarcely has any impact on the output of the recommendation while guaranteeing a supplementary secure channel for transmitting user-based gradients back and forth the global server. The result of this analysis indicates that the performance of federated stochastic modification minimized gradient (FSMMG) algorithm is greatly increased at every given increase in the number of users and a good convergence is achieved as well. Also, experiments indicate that when compared against other existing techniques, the proposed FSMMG outperforms at 98.3% encryption accuracy.

Blockchain-Secured Recommender System for Special Need Patients Using Deep Learning.

Recommender systems offer several advantages to hospital data management units and patients with special needs. These systems are more dependent on the extreme subtle hospital-patient data. Thus, disregarding the confidentiality of patients with special needs is not an option. In recent times, several proposed techniques failed to cryptographically guarantee the data privacy of the patients with special needs in the diet recommender systems (RSs) deployment. In order to tackle this pitfall, this paper incorporates a blockchain privacy system (BPS) into deep learning for a diet recommendation system for patients with special needs. Our proposed technique allows patients to get notifications about recommended treatments and medications based on their personalized data without revealing their confidential information. Additionally, the paper implemented machine and deep learning algorithms such as RNN, Logistic Regression, MLP, etc., on an Internet of Medical Things (IoMT) dataset acquired via the internet and hospitals that comprises the data of 50 patients with 13 features of various diseases and 1,000 products. The product section has a set of eight features. The IoMT data features were analyzed with BPS and further encoded prior to the application of deep and machine learning-based frameworks. The performance of the different machine and deep learning methods were carried out and the results verify that the long short-term memory (LSTM) technique is more effective than other schemes regarding prediction accuracy, precision, F1-measures, and recall in a secured blockchain privacy system. Results showed that 97.74% accuracy utilizing the LSTM deep learning model was attained. The precision of 98%, recall, and F1-measure of 99% each for the allowed class was also attained. For the disallowed class, the scores were 89, 73, and 80% for precision, recall, and F1-measure, respectively. The performance of our proposed BPS is subdivided into two categories: the secured communication channel of the recommendation system and an enhanced deep learning approach using health base medical dataset that spontaneously identifies what food a patient with special needs should have based on their disease and certain features including gender, weight, age, etc. The proposed system is outstanding as none of the earlier revised works of literature described a recommender system of this kind.

The Use of Ensemble Models for Multiple Class and Binary Class Classification for Improving Intrusion Detection Systems.

The pursuit to spot abnormal behaviors in and out of a network system is what led to a system known as intrusion detection systems for soft computing besides many researchers have applied machine learning around this area. Obviously, a single classifier alone in the classifications seems impossible to control network intruders. This limitation is what led us to perform dimensionality reduction by means of correlation-based feature selection approach (CFS approach) in addition to a refined ensemble model. The paper aims to improve the Intrusion Detection System (IDS) by proposing a CFS + Ensemble Classifiers (Bagging and Adaboost) which has high accuracy, high packet detection rate, and low false alarm rate. Machine Learning Ensemble Models with base classifiers (J48, Random Forest, and Reptree) were built. Binary classification, as well as Multiclass classification for KDD99 and NSLKDD datasets, was done while all the attacks were named as an anomaly and normal traffic. Class labels consisted of five major attacks, namely Denial of Service (DoS), Probe, User-to-Root (U2R), Root to Local attacks (R2L), and Normal class attacks. Results from the experiment showed that our proposed model produces 0 false alarm rate (FAR) and 99.90% detection rate (DR) for the KDD99 dataset, and 0.5% FAR and 98.60% DR for NSLKDD dataset when working with 6 and 13 selected features.

Realizing Efficient Security and Privacy in IoT Networks.

In recent times, security and privacy at the physical (PHY) layer has been a major issue of several communication technologies which comprise the internet of things (IoT) and mostly, the emerging fifth-generation (5G) cellular network. The most real-world PHY security challenge stems from the fact that the passive eavesdropper's information is unavailable to the genuine source and destination (transmitter/receiver) nodes in the network. Without this information, it is difficult to optimize the broadcasting parameters. Therefore, in this research, we propose an efficient sequential convex estimation optimization (SCEO) algorithm to mitigate this challenge and improve the security of physical layer (PHY) in a three-node wireless communication network. The results of our experiments indicate that by using the SCEO algorithm, an optimal performance and enhanced convergence is achieved in the transmission. However, considering possible security challenges envisaged when a multiple eavesdropper is active in a network, we expanded our research to develop a swift privacy rate optimization algorithm for a multiple-input, multiple-output, multiple-eavesdropper (MIMOME) scenario as it is applicable to security in IoT and 5G technologies. The result of the investigation show that the algorithm executes significantly with minimal complexity when compared with nonoptimal parameters. We further employed the use of rate constraint together with self-interference of the full-duplex transmission at the receiving node, which makes the performance of our technique outstanding when compared with previous studies.

Hafnia alvei pneumonia: a rare cause of infection in the multimorbid or immunocompromised.

Hafnia alvei is a rare, poorly understood commensal bacterium which has, on occasion, been shown to infect humans. We present two cases. The first patient presented with a 1-week history of dyspnoea, pleurisy and a productive cough, and the second with a prodrome of fatigue and night sweats. The former had a history of severe chronic obstructive pulmonary disease and the latter had a history of Crohn's disease. Both patients had underlying comorbidities and immunosuppression, but differed in presentation, radiological findings and recovery. This case series aims to remind readers of the broad differential of pathogens that can lead to disease in the immunocompromised and that one should not dismiss atypical cultured bacteria as commensal too hastily.

Attitudes of Older Chinese Patients Toward Death and Dying.

BACKGROUND: Due to the aging population of China, the need for palliative care will increase. However, one of the barriers to utilization of palliative care is the traditional belief that talking about death and dying is taboo. OBJECTIVE: The aim of this study was to examine to what extent older Chinese patients were willing to answer questions about death and dying by asking them about "fear of death" and their desire to "use advanced life support when dying." DESIGN: Survey questionnaire. SETTING/SUBJECTS: Convenience sample (N = 993 hospitalized patients). RESULTS: Only 215 (21.7%; 95% confidence interval [CI] 16.2%-27.1%) and 99 (9.9%; 95% CI 4.1%-15.8%) patients did not answer the questions related to "fear of death" and "use of advanced life support when dying," respectively, while 439 (44.2%; 95% CI 38.7%-49.7%) answered "yes" and 339 (34.1%; 95% CI 28.7%-39.6%) answered "no" for "fear of death" and 382 (38.5%; 95% CI 32.6%-44.3%) answered "yes" and 512 (51.6%; 95% CI 45.7%-57.4%) answered "no" for "use of advanced life support when dying." In multinomial logistic regression analysis, fear of death was associated with younger age, lowest level of function, and desire to use advanced life support. CONCLUSIONS: The majority of older patients were willing to answer the two questions about death and dying. About one-third of patients were not afraid of death, and older patients were less likely to be afraid of death. More than 50% of patients answered that they would not choose advanced life support when dying. More research in this area is needed to help advance palliative care in China.

Antifungal activity of 10 Guadeloupean plants.

Screening of the antifungal activities of ten Guadeloupean plants was undertaken to find new extracts and formulations against superficial mycoses such as onychomycosis, athlete's foot, Pityriasis versicolor, as well as the deep fungal infection Pneumocystis pneumonia. For the first time, the CMI of these plant extracts [cyclohexane, ethanol and ethanol/water (1:1, v/v)] was determined against five dermatophytes, five Candida species, Scytalidium dimidiatum, a Malassezia sp. strain and Pneumocystis carinii. Cytotoxicity tests of the most active extracts were also performed on an HaCat keratinocyte cell line. Results suggest that the extracts of Bursera simaruba, Cedrela odorata, Enterolobium cyclocarpum and Pluchea carolinensis have interesting activities and could be good candidates for developing antifungal formulations.

Antifungal and cytotoxic activity of withanolides from Acnistus arborescens.

Three compounds were isolated from Acnistus arborescens, a tree commonly used in South and Central America in traditional medicine against several infectious diseases, some of which are caused by fungi. Bioassay-guided fractionation of a MeOH extract of leaves, based on its anti-Pneumocystis carinii activity, led to the isolation of compounds 1-3. Mono- and bidimensional NMR analyses enabled identification of two new withanolides, (20R,22R)-5beta,6beta-epoxy-4beta,12beta,20-trihydroxy-1-oxowith-2-en-24-enolide (1) and (20R,22R)-16beta-acetoxy-3beta,4beta;5beta,6beta-diepoxy-12beta,20-dihydroxy-1-oxowith-24-enolide (2), and withanolide D (3). Antifungal activity on 13 fungi responsible for human infections (five dermatophytes, one nondermatophyte mold, six yeasts, and Pneumocystis carinii) was examined. Cytotoxicity of these compounds was also evaluated in vitro.

Development and evaluation of 'neck pain and functional limitation scale': a validation study in the Asian context.

BACKGROUND: There is a paucity of literature on validated outcome measurement tools for evaluation of neck pain and related disability in the Asian context. AIM: The main aim of the present study was to design a new tool called neck pain functional limitation scale (NPFLS) for measuring disability related to neck pain and observe its reliability, concurrent validity and criterion validity. SETTING AND DESIGN: This study was performed at the institutional hospital. MATERIALS AND METHODS: A total of 157 subjects (neck pain group) and 25 control subjects (control group) without neck pain were recruited for this study. NPFLS was framed as a new tool for this study, which consisted of 5 domains - pain intensity, activities of daily living, social activities, functional activities and psychological factors. Neck Bournemouth questionnaire (NBQ) was used as a gold standard to measure the concurrent validity and criterion validity of the NPFLS. STATISTICAL ANALYSIS: Criterion validity and concurrent validity between the neck Bournemouth questionnaire (NBQ) and NPFLS scores were tested statistically using Mann-Whitney U test and Spearman correlation test. The reliability was tested by examining the internal consistency to calculate the Cronbach's alpha value for each item in NPFLS. RESULTS: No significant difference between NPFLS and NBQ was observed using Mann-Whitney U Test, with P value greater than 0.05 (P= 0.557). Besides that, NPFLS had a high concurrent validity (r= 0.916) and good internal consistency with high Cronbach's alpha value of (r= 0.948), which demonstrated strong correlation between the items of NPFLS and NBQ. CONCLUSION: NPFLS demonstrated good reliability, high concurrent validity and criterion validity in this study. NPFLS can be used to assess neck pain and disability among patients with neck pain.

The CHRNA5-CHRNA3-CHRNB4 nicotinic receptor subunit gene cluster affects risk for nicotine dependence in African-Americans and in European-Americans.

Genetic association studies have shown the importance of variants in the CHRNA5-CHRNA3-CHRNB4 cholinergic nicotinic receptor subunit gene cluster on chromosome 15q24-25.1 for the risk of nicotine dependence, smoking, and lung cancer in populations of European descent. We have carried out a detailed study of this region using dense genotyping in both European-Americans and African-Americans. We genotyped 75 known single nucleotide polymorphisms (SNPs) and one sequencing-discovered SNP in an African-American sample (N = 710) and in a European-American sample (N = 2,062). Cases were nicotine-dependent and controls were nondependent smokers. The nonsynonymous CHRNA5 SNP rs16969968 is the most significant SNP associated with nicotine dependence in the full sample of 2,772 subjects [P = 4.49 x 10(-8); odds ratio (OR), 1.42; 95% confidence interval (CI), 1.25-1.61] as well as in African-Americans only (P = 0.015; OR, 2.04; 1.15-3.62) and in European-Americans only (P = 4.14 x 10(-7); OR, 1.40; 1.23-1.59). Other SNPs that have been shown to affect the mRNA levels of CHRNA5 in European-Americans are associated with nicotine dependence in African-Americans but not in European-Americans. The CHRNA3 SNP rs578776, which has a low correlation with rs16969968, is associated with nicotine dependence in European-Americans but not in African-Americans. Less common SNPs (frequency

Senna alata.

A review is made of chemical, ethnopharmacological and pharmacological papers dealing with Senna alata (L.) Roxb., a plant that belongs to the Creole traditional system of medicine and that has recently been introduced in the French Pharmacopoeia. The proofs existing for its various usages are presented. The species is mainly used against constipation and skin diseases. The laxative activity is supported by scientific findings. In contrast the dermatologic use requires further investigation. The species can be considered as safe for short-term or topical use.

Ethnopharmacology of Lippia alba.

INTRODUCTION: Chemical, ethnopharmacological and pharmacological research on Lippia alba (Mill.) N.E. Brown and the evidence that exists for its various usages have been looked for, focusing on high quality studies. ETHNOPHARMACOLOGICAL INVESTIGATION: The species is mainly used against digestive and respiratory ailments, and as a sedative and antihypertensive remedy. CHEMICAL CONSTITUENTS: Seven chemotypes exist for the essential oil, the non-volatile compounds are iridioids, phenylethanoids, flavone glycosides and biflavonoids. BIOLOGICAL ACTIVITIES AND ETHNOPHARMACOLOGICAL APPRAISAL: Some positive, although partial, results have been obtained on sedative and anxiolytic activities. Real effects in other traditional uses can mainly be explained by anti-infectious and analgesic properties, at the moment. CONCLUSION: Well conducted biological studies are still needed for several indications of this species. Its use as a sedative deserves a clinical investigation. The chemical variability of the species seems important both in the essential oil and in non-volatile compounds, so future research on the pharmacological properties of these extracts should provide more chemical data which will increase their validity.

Antioxidant and neurosedative properties of polyphenols and iridoids from Lippia alba.

The neurosedative and antioxidative properties of some major compounds isolated from a citral chemotype of Lippia alba were investigated. Binding assays were performed on two CNS inhibitory targets: benzodiazepine and GABA(A) receptors. The most active compound was luteolin-7-diglucuronide, with half maximal inhibitory concentrations (IC(50)) of 101 and 40 microm, respectively. Fifteen compounds isolated from Lippia alba were tested for their radical scavenging capacities against DPPH. Four of the major compounds (verbascoside, calceolarioside E, luteolin-7-diglucuronide and theveside) were also tested for their antioxidant activity against superoxide radical-anion in cell-free (hypoxanthine-xanthine oxidase) and cellular (PMA-stimulated neutrophil granulocytes) systems.

China: the aging giant.

This article examines the changing demographics of China, with particular attention paid to the effect of the one-child policy in relation to long-term care of older people. It also examines the current state of health care for older people. Long-term stays characterize hospital care. Most geriatric syndromes are less common in hospitalized older people (e.g., delirium, falls), but some (e.g., polypharmacy) are more common. A high volume of patients and brief targeted visits characterize outpatient care. Nursing homes exist in China, but relatively fewer than in the most developed countries. Geriatric departments in university-based hospitals primarily have developed out of a need to care for retired government officials and workers. There are no formal geriatric fellowships or national board certifications in geriatrics Health care is primarily based on fee for service. Not all elderly have healthcare insurance. Although costs of health care and medications are less expensive than in the United States, they are relatively high for lower- and middle-class Chinese and have increased more quickly than has the standard of living in the past 20 years. Family and community support for older people is strong in China. Some older people have one-to-one care from a baomu (literally "protection" (bao) "mother" (mu)), a type of live-in maid who also provides care for the older person. Some of the challenges facing China in the care of its aging population are how to increase geriatric research and training, how to care for the uninsured or underinsured, and how to handle the inevitable growth of disabled and frail older people.

The essential oil of Lippia alba: analysis of samples from French overseas departments and review of previous works.

This paper contains new data on the chemical composition of the essential oil of Lippia alba (Mill.) N. E. Brown, as well as an overview of the available literature. Although the composition of the essential oil of this species is well-documented, discrepancies between the reported results suggest that many chemotypes and morphotypes exist. The analysis of essential oils obtained from the leaves of samples from three different locations in the French Overseas Departments (French Guiana, Martinique, and two different places in Guadeloupe) have shown that the composition of each one is quite different. This new data, along with a review and discussion of published studies, enabled us to establish seven distinct chemotypes. Possible connections between these chemotypes and morphotypes already described were also investigated.

Composition of fatty acids triacylglycerols and unsaponifiable matter in Calophyllum calaba L. oil from Guadeloupe.

The composition of the kernel oils of two Calophyllum species (Calophyllum calaba L. and Calophyllum inophyllum L.) was investigated. The physico-chemical properties and fatty acid composition of the kernel oils were examined. In two species, oleic acid C18:1 (39.1-50%) is the dominating fatty acid followed by linoleic acid C18:2 (21.7-31.1%) as the second major fatty acid. Stearic C18:0 (13.4-14.3%) and palmitic C16:0 (11-13.7%) acids are the major saturates. The oils contains an appreciable amount of unsaturated fatty acids (70.8-73.10%). Most of the fatty acids are present as triacylglycerol (76.7-84%), twenty one triacylglycerols are detected with predominantly unsaturated triacylglycerols. The total unsaponifiable content, its general composition and the identity of the components of the sterol and tocopherol fractions are presented. In both species, analysis of the unsaponifiable fractions revealed the preponderance of phytosterols, mainly stigmasterol (35.8-45.1%) and beta-sitosterol (41.1-43.1%). Among the eight tocopherols and tocotrienols present in two species, variations exist; alpha-tocopherol (183 mg/kg) is the main tocopherol in Calophyllum calaba L. and Delta-tocotrienol (236 mg/kg) is the dominant tocotrienol in Calophyllum inophyllum L.