Artificial Intelligence;a Pragmatic Approach to Implementation in Medicine, a Review of the literature and a Survey of Local Practice in Midlands in UK

The use of Artificial Intelligence (AI) for clinical pathway management and decision making is believed to improve clinical care and has been used to improve pathways for treatment in most medical disciplines. Methods: A literature review was undertaken to identify the hurdles and steps required to introduce supported clinical decision-making using AI within hospitals. This was supported by a survey of local hospital practice within the Midlands of the United Kingdom to see what systems had been introduced and were functioning effectively. Results: It is unclear how to practically implement systems using AI within medicine easily. Algorithmic medicine based on a set of rules calculated from data only takes a clinician so far to deliver patient centred optimal treatment. AI facilitates a clinician’s ability to assimilate data from disparate sources and can help with some of the analysis and decision making. However, learning remains organic and the subtleties of difference between patients, care providers who exhibit non-verbal communication for instance make it difficult for an AI to capture all the pertinent information required to make the correct clinical decision for any given individual. Hence it assists rather than controls any process in clinical practice. It also must continually renew and adapt considering changes in practise and trends as the goalposts change to meet fluctuations in resources and workload. Precision surgery is benefiting from robotic-assisted surgery in parts driven by AI and being used in 80% of trusts locally. Conclusion: The use of AI in clinical practice remains patchy with it being adopted where research groups have studied a more effective method of monitoring or treatment. The use of robotic-assisted surgery on the other hand has been more rapid as the precision of treatment that this provides appears attractive in improving clinical care.

Genome-wide investigation to assess copy number variants in the Italian local chicken population

Background Copy number variants(CNV)hold significant functional and evolutionary importance.Numerous ongoing CNV studies aim to elucidate the etiology of human diseases and gain insights into the population structure of livestock.High-density chips have enabled the detection of CNV with increased resolution,leading to the identification of even small CNV.This study aimed to identify CNV in local Italian chicken breeds and investigate their distribution across the genome.Results Copy number variants were mainly distributed across the first six chromosomes and primarily associated with loss type CNV.The majority of CNV in the investigated breeds were of types 0 and 1,and the minimum length of CNV was significantly larger than that reported in previous studies.Interestingly,a high proportion of the length of chromosome 16 was covered by copy number variation regions(CNVR),with the major histocompatibility complex being the likely cause.Among the genes identified within CNVR,only those present in at least five animals across breeds(n=95)were discussed to reduce the focus on redundant CNV.Some of these genes have been associated to functional traits in chickens.Notably,several CNVR on different chromosomes harbor genes related to muscle development,tissue-specific biological processes,heat stress resistance,and immune response.Quantitative trait loci(QTL)were also analyzed to investigate potential overlapping with the identified CNVR:54 out of the 95 gene-containing regions overlapped with 428 QTL associated to body weight and size,carcass characteristics,egg production,egg components,fat deposition,and feed intake.Conclusions The genomic phenomena reported in this study that can cause changes in the distribution of CNV within the genome over time and the comparison of these differences in CNVR of the local chicken breeds could help in preserving these genetic resources.

Present situation and prospect of immunotherapy for unresectable locally advanced esophageal cancer during peri-radiotherapy

Four major studies(Checkmate577,Keynote-590,Checkmate649 and Attraction-4)of locally advanced esophageal cancer published in 2020 have established the importance of immunotherapy,represented by anti-programmed death protein(PD)-1 in postoperative adjuvant treatment and advanced first-line treatment of locally advanced or advanced esophageal cancer and esophagogastric junction cancer,from the aspects of proof of concept,long-term survival,overall survival rate and progression-free survival.For unresectable or inoperable nonmetastatic esophageal cancer,concurrent radiotherapy and chemotherapy is the standard treatment recommended by various guidelines.Because its curative effect is still not ideal,it is necessary to explore radical radiotherapy and chemotherapy in the future,and it is considered to be promising to combine them with immunotherapeutic drugs such as anti-PD-1.This paper mainly discusses how to combine radical concurrent radiotherapy and chemotherapy with immunotherapy for unresectable local advanced esophageal cancer.

Deep brain implantable microelectrode arrays for detection and functional localization of the subthalamic nucleus in rats with Parkinson’s disease

The subthalamic nucleus(STN)is considered the best target for deep brain stimulation treatments of Parkinson’s disease(PD).It is difficult to localize the STN due to its small size and deep location.Multichannel microelectrode arrays(MEAs)can rapidly and precisely locate the STN,which is important for precise stimulation.In this paper,16-channel MEAs modified with multiwalled carbon nanotube/poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate)(MWCNT/PEDOT:PSS)nanocomposites were designed and fabricated,and the accurate and rapid identification of the STN in PD rats was performed using detection sites distributed at different brain depths.These results showed that nuclei in 6-hydroxydopamine hydrobromide(6-OHDA)-lesioned brains discharged more intensely than those in unlesioned brains.In addition,the MEA simultaneously acquired neural signals from both the STN and the upper or lower boundary nuclei of the STN.Moreover,higher values of spike firing rate,spike amplitude,local field potential(LFP)power,and beta oscillations were detected in the STN of the 6-OHDA-lesioned brain,and may therefore be biomarkers of STN localization.Compared with the STNs of unlesioned brains,the power spectral density of spikes and LFPs synchronously decreased in the delta band and increased in the beta band of 6-OHDA-lesioned brains.This may be a cause of sleep and motor disorders associated with PD.Overall,this work describes a new cellular-level localization and detection method and provides a tool for future studies of deep brain nuclei.

The evolution of cancer genomic medicine in Japan and the role of the National Cancer Center Japan

The journey to implement cancer genomic medicine(CGM)in oncology practice began in the 1980s,which is considered the dawn of genetic and genomic cancer research.At the time,a variety of activating oncogenic alterations and their functional significance were unveiled in cancer cells,which led to the development of molecular targeted therapies in the 2000s and beyond.Although CGM is still a relatively new discipline and it is difficult to predict to what extent CGM will benefit the diverse pool of cancer patients,the National Cancer Center(NCC)of Japan has already contributed considerably to CGM advancement for the conquest of cancer.Looking back at these past achievements of the NCC,we predict that the future of CGM will involve the following:1)A biobank of paired cancerous and non-cancerous tissues and cells from various cancer types and stages will be developed.The quantity and quality of these samples will be compatible with omics analyses.All biobank samples will be linked to longitudinal clinical information.2)New technologies,such as whole-genome sequencing and artificial intelligence,will be introduced and new bioresources for functional and pharmacologic analyses(e.g.,a patient-derived xenograft library)will be systematically deployed.3)Fast and bidirectional translational research(bench-to-bedside and bedside-to-bench)performed by basic researchers and clinical investigators,preferably working alongside each other at the same institution,will be implemented;4)Close collaborations between academia,industry,regulatory bodies,and funding agencies will be established.5)There will be an investment in the other branch of CGM,personalized preventive medicine,based on the individual's genetic predisposition to cancer.

Globalization and Glocalization in the History of Chinese Medicine

The globalization of Chinese medicine, forged through successive waves of migration, cultural exchanges, and economic imperatives, constitutes a nuanced and intricate process with historical roots extending over millennia. It stands as the culmination of interconnected historical events that reverberated beyond the confines of China, emerging as a phenomenon characterized by the adjustment of Chinese medical theories, clinical practices, and materia medica to indigenous customs and healthcare traditions prevalent in both proximate and distant regions. In these glocalized processes, the global and the local intersect and mix. The frameworks of globalization and glocalization allow a critical interpretation of the many hybridizations that have shaped overseas Chinese medicine's history and present.

Application of integrated traditional Chinese and Western medicine in the treatment of juvenile localized scleroderma with skin ulcer: a case report

Background:Juvenile Localized Scleroderma(JLS)is a rare pediatric rheumatic disease characterized by inflammation and skin sclerosis.The side effect of consensus-recommended medications and the risk of disability posed challenges to the JLS treatment.We intend to demonstrate the potential of traditional Chinese medicine in treating JLS with skin ulcers and reducing the dose of glucocorticoid.Method:Here we report a case of a 13-year-old male with JLS who took oral methotrexate tablets of 10 mg/week and methylprednisolone of 6 mg/day for over six months without significant effect and suffered from skin ulcers on the dorsal feet one month after drug cessation.Subsequently,the patient was treated with integrated traditional Chinese and Western medicine of low-dose glucocorticosteroid,adjusted Shenqi Huoxue formula and Jinshe Xiaoyan formula,etc.Results:After integrated treatment,the patient’s dorsal feet ulcers healed and the skin sclerosis and hyperpigmentation improved significantly.Conclusions:This case report suggests that integrated traditional Chinese and Western medicine can be used as an effective treatment for JLS.

Assessment of earthquake location uncertainties for the design of local seismic networks

The ability to estimate earthquake source locations,along with the appraisal of relevant uncertainties,is paramount in monitoring both natural and human-induced micro-seismicity.For this purpose,a monitoring network must be designed to minimize the location errors introduced by geometrically unbalanced networks.In this study,we first review different sources of errors relevant to the localization of seismic events,how they propagate through localization algorithms,and their impact on outcomes.We then propose a quantitative method,based on a Monte Carlo approach,to estimate the uncertainty in earthquake locations that is suited to the design,optimization,and assessment of the performance of a local seismic monitoring network.To illustrate the performance of the proposed approach,we analyzed the distribution of the localization uncertainties and their related dispersion for a highly dense grid of theoretical hypocenters in both the horizontal and vertical directions using an actual monitoring network layout.The results expand,quantitatively,the qualitative indications derived from purely geometrical parameters(azimuthal gap(AG))and classical detectability maps.The proposed method enables the systematic design,optimization,and evaluation of local seismic monitoring networks,enhancing monitoring accuracy in areas proximal to hydrocarbon production,geothermal fields,underground natural gas storage,and other subsurface activities.This approach aids in the accurate estimation of earthquake source locations and their associated uncertainties,which are crucial for assessing and mitigating seismic risks,thereby enabling the implementation of proactive measures to minimize potential hazards.From an operational perspective,reliably estimating location accuracy is crucial for evaluating the position of seismogenic sources and assessing possible links between well activities and the onset of seismicity.

SNR and RSSI Based an Optimized Machine Learning Based Indoor Localization Approach:Multistory Round Building Scenario over LoRa Network

In situations when the precise position of a machine is unknown,localization becomes crucial.This research focuses on improving the position prediction accuracy over long-range(LoRa)network using an optimized machine learning-based technique.In order to increase the prediction accuracy of the reference point position on the data collected using the fingerprinting method over LoRa technology,this study proposed an optimized machine learning(ML)based algorithm.Received signal strength indicator(RSSI)data from the sensors at different positions was first gathered via an experiment through the LoRa network in a multistory round layout building.The noise factor is also taken into account,and the signal-to-noise ratio(SNR)value is recorded for every RSSI measurement.This study concludes the examination of reference point accuracy with the modified KNN method(MKNN).MKNN was created to more precisely anticipate the position of the reference point.The findings showed that MKNN outperformed other algorithms in terms of accuracy and complexity.

Survey of Indoor Localization Based on Deep Learning

This study comprehensively examines the current state of deep learning (DL) usage in indoor positioning.It emphasizes the significance and efficiency of convolutional neural networks (CNNs) and recurrent neuralnetworks (RNNs). Unlike prior studies focused on single sensor modalities like Wi-Fi or Bluetooth, this researchexplores the integration of multiple sensor modalities (e.g.,Wi-Fi, Bluetooth, Ultra-Wideband, ZigBee) to expandindoor localization methods, particularly in obstructed environments. It addresses the challenge of precise objectlocalization, introducing a novel hybrid DL approach using received signal information (RSI), Received SignalStrength (RSS), and Channel State Information (CSI) data to enhance accuracy and stability. Moreover, thestudy introduces a device-free indoor localization algorithm, offering a significant advancement with potentialobject or individual tracking applications. It recognizes the increasing importance of indoor positioning forlocation-based services. It anticipates future developments while acknowledging challenges such as multipathinterference, noise, data standardization, and scarcity of labeled data. This research contributes significantly toindoor localization technology, offering adaptability, device independence, and multifaceted DL-based solutionsfor real-world challenges and future advancements. Thus, the proposed work addresses challenges in objectlocalization precision and introduces a novel hybrid deep learning approach, contributing to advancing locationcentricservices.While deep learning-based indoor localization techniques have improved accuracy, challenges likedata noise, standardization, and availability of training data persist. However, ongoing developments are expectedto enhance indoor positioning systems to meet real-world demands.

Re-evaluating the role of pelvic radiation in the age of modern precision medicine and systemic therapy

The efficacy of pelvic radiation in the management of locally advanced stage rectal cancer has come under scrutiny in the context of modern precision medicine and systemic therapy as evidenced by recent clinical trials such as FOWARC(J Clin Oncol 2019;37:3223-3233),NCT04165772(N Engl J Med 2022;386:2363-2376),and PROSPECT(N Engl J Med 2023;389:322-334).In this review,we comprehensively assess these pivotal trials and offer additional insights into the evolving role of pelvic radiation in contemporary oncology.

Seropositivity and Other Determinants Associated with Toxoplasmosis in Local Buffalo in Iraq

A cross-sectional study was conducted to determine the Seropositivity of Toxoplasma gondii in water buffalo in three Iraqi governorates (Baghdad, Dhi Qar, and Maysan) and to estimate the risk aspects related to infestation throughout the period from January to December 2019. A total of 430 serum samples were inspected with a commercial ELISA (Enzyme linked immunosorbent assay) kit. Indirect multi-species kit. The overall Seropositivity of T. gondii in the examined local buffalo was 7.4%, and the highest rate (9.3%) was in Baghdad Governorate. A multivariate regression analysis revealed that adult buffalo (OR = 7.10;95% CI: 0.87-57.68;P = 0.067) and young herds (OR = 8.42;95% CI: 1.07-66.02;P = 0.043) were more subject to infestation from young buffalo and large herds. Furthermore, the hazard of toxoplasmosis was increased in winter especially among animals in contact with cats. It is therefore requisite to determine risk aspects to evaluate which mitigation, control, prevention and procedures should be carried out to diminish, control and prevent infestation with T. gondii and its propagation.

Integration of traditional,complementary,and alternative medicine with modern biomedicine:the scientization,evidence,and challenges for integration of traditional Chinese medicine

Traditional medicine has garnered significant global recognition,with an estimated 80%of the global population using it.Therefore,it is essential to fully understand the integration of traditional medicines into current healthcare systems.This review aims to provide a comprehensive overview of the standard process to modernize traditional medicine scientifically in the context of modern biomedicine,further termed here as“scientization”.Specifically,we aim to summarize the advancements made in understanding the efficacy,effectiveness,and underlying mechanisms of herbal medicine.We also examined the transition from experience-to evidence-based medicine during acupuncture.Furthermore,we explore the development of universal safety and quality control standards.Finally,we discuss international trade and export markets for Chinese medical products.The development and integration of traditional medicine have allowed it to further improve human health,resulting in a more comprehensive health solution for the global population.

Improved PSO-Extreme Learning Machine Algorithm for Indoor Localization

Wi Fi and fingerprinting localization method have been a hot topic in indoor positioning because of their universality and location-related features.The basic assumption of fingerprinting localization is that the received signal strength indication(RSSI)distance is accord with the location distance.Therefore,how to efficiently match the current RSSI of the user with the RSSI in the fingerprint database is the key to achieve high-accuracy localization.In this paper,a particle swarm optimization-extreme learning machine(PSO-ELM)algorithm is proposed on the basis of the original fingerprinting localization.Firstly,we collect the RSSI of the experimental area to construct the fingerprint database,and the ELM algorithm is applied to the online stages to determine the corresponding relation between the location of the terminal and the RSSI it receives.Secondly,PSO algorithm is used to improve the bias and weight of ELM neural network,and the global optimal results are obtained.Finally,extensive simulation results are presented.It is shown that the proposed algorithm can effectively reduce mean error of localization and improve positioning accuracy when compared with K-Nearest Neighbor(KNN),Kmeans and Back-propagation(BP)algorithms.

Research on the development methodology for clinical practice guidelines for organic integration of traditional Chinese medicine and Western medicine

Integrated traditional Chinese medicine(TCM)and Western medicine(WM)is a new medical science grounded in the knowledge bases of both TCM and WM,which then forms a unique modern medical system in China.Integrated TCM and WM has a long history in China,and has made important achievements in the process of clinical diagnosis and treatment.However,the methodological defects in currently published clinical practice guidelines(CPGs)limit its development.The organic integration of TCM and WM is a deeper integration of TCM and WM.To realize the progression of"integration"to"organic integration",a targeted and standardized guideline development methodology is needed.Therefore,the purpose of this study is to establish a standardized development procedure for clinical practice guidelines for the organic integration of TCM and WM to promote the systematic integration of TCM and WM research results into clinical practice guidelines in order to achieve optimal results as the whole is greater than the sum of the parts.

Chinese Medicine,Acupuncture and Science

Ever since the introduction of Western biomedicine into China, there has been friction between proponents of this new approach, and proponents of the traditional medical practices that had evolved over thousands of years in China. For the most part, this friction has been couched in the unexamined assumption that Western medicine is based on science, while Chinese medicine is not. This article will examine that assumption, which in this author’s opinion is unjustified and incorrect. Having practiced acupuncture for the past 50 years, after receiving my doctoral degrees in medicine and physiology, my thinking on this topic has also evolved over time. I will begin this article with some historical information that bears on the topic under discussion, followed by my personal ideas about how to resolve the confiicts that have arisen.

Model informed precision medicine of Chinese herbal medicines formulas-A multi-scale mechanistic intelligent model

Recent trends suggest that Chinese herbal medicine formulas(CHM formulas)are promising treatments for complex diseases.To characterize the precise syndromes,precise diseases and precise targets of the precise targets between complex diseases and CHM formulas,we developed an artificial intelligence-based quantitative predictive algorithm(DeepTCM).DeepTCM has gone through multilevel model calibration and validation against a comprehensive set of herb and disease data so that it accurately captures the complex cellular signaling,molecular and theoretical levels of traditional Chinese medicine(TCM).As an example,our model simulated the optimal CHM formulas for the treatment of coronary heart disease(CHD)with depression,and through model sensitivity analysis,we calculated the balanced scoring of the formulas.Furthermore,we constructed a biological knowledge graph representing interactions by associating herb-target and gene-disease interactions.Finally,we experimentally confirmed the therapeutic effect and pharmacological mechanism of a novel model-predicted intervention in humans and mice.This novel multiscale model opened up a new avenue to combine“disease syndrome”and“macro micro”system modeling to facilitate translational research in CHM formulas.

Study of the Management and Disposal Practices of Unused or Out-of-Date Medicines by Households in the Municipality of Ouagadougou, Burkina Faso

Introduction: Not all medicines that pass-through consumers’ hands are used, and some often expire in households. These health products can be sources of accidental risks and pollution when they are not properly disposed of. In Burkina Faso, there are as yet no guidelines for the disposal of unused medicines in households. The aim of this study was to estimate the extent of household possession of unused or expired medicines, and to describe attitudes and disposal practices. Methods: This was a descriptive cross-sectional study covering households in the Ouagadougou commune conducted from June to August 2021. Two-stage stratified sampling was used: selection of Enumeration Zones (EZs) and selection of households, with each EZ comprising several households. Data collection was based on direct interviews using a structured questionnaire. Data were processed using Epi Info software version 7.2.4.0. Results: In total, 417 household residents were surveyed out of the planned 423 households, corresponding to a completion rate of 98.58% compared with the initial sample. Among the respondents, 79.62% had unused and/or expired medicines in their household. A total of 2562 drug packaging units were counted, for a total weight of 121.90 kg. Nearly 75% were aware that improper disposal was a danger to the environment. Some respondents kept their unused medicines at home until they expired (43.41%), and disposed of them mainly by throwing them in the household garbage (75.58%). The majority (79%) were in favor of the government setting up a take-back program for these medicines. Conclusion: The introduction of a take-back program for unused or out-of-date medicines will ensure safer disposal of medicines, and better protection for households and the environment.

Research progress of traditional Chinese medicine in the treatment of endocrine metabolic diseases in 2023

This study aimed to provide a comprehensive review of the research progress in Chinese medicine in the treatment of endocrine metabolic diseases in 2023,covering traditional Chinese medicine(TCM)monomers,TCM extracts,and TCM combinations,including non-alcoholic fatty liver disease,type 2 diabetes mellitus and its complications,obesity,hyperuricaemia,and thyroid disorders.After systematic sorting and summary,we found that in 2023,the research focusing on the application of TCM for endocrine metabolic diseases was still on the mechanism of action at the cellular and molecular levels,which not only influenced the classical pathways of lipid metabolism,but also delved into the key mechanisms of anti-inflammation,anti-oxidation,anti-insulin resistance,and so on.Additionally,TCM has shown remarkable results in the treatment of endocrine metabolic diseases by improving intestinal flora disorders and abnormal cellular iron death.These research results provide valuable ideas,methods,and tools for TCM in the prevention and treatment of endocrine metabolic diseases,and provide important references and guidance for future research and practice.

Chen Shigong,Founder of“TCM Orthodox School of External Medicine”

Chen Shigong,styled name Yuren,was also known by the literary name Ruoxu.Coming from Donghaichongchuan(present Nantong City,Jiangsu Province)he was a famous traditional Chinese medicine(TCM)specialist of external medicine of the Ming Dynasty(1368-1644).The Orthodox Lineage of External Medicine(Wai Ke Zheng Zong)written by him has been valued as the founder of the TCM Orthodox School of External Medicine.