This article was migrated. The article was marked as recommended.Background: Recently, the orthopaedic surgery PGY-1 curriculum was redesigned to maximize time spent on orthopaedic surgery rotations. Additionally, surgical skills modules were introduced to standardize curricula for orthopaedic interns in the United States.Objective: The purpose of this study is to determine the implementation of the curriculum guidelines were implemented on a national level.Methods: An anonymous survey with 14 multiple choice questions was electronically distributed to program directors (PDs) for all ACGME-accredited orthopaedic surgery residency programs in the US (n=163) in January 2017. Seventy-nine of the 162 PDs (49%) completed the survey in its entirety.Results: The most common non-orthopaedic rotations included: general surgery trauma (67/79=85%), surgical/medical intensive care unit (60/79=76%), plastic and burn surgery (56/79=71%), musculoskeletal radiology (44/79=56%), and vascular surgery (40/79=51%). Seventy-two of 162 residency programs (91%) have a formal surgical skills curriculum for first-year residents, separate from intern boot camp. A variety of training modalities were utilized to teach the interns, most commonly saw bones for fracture fixation (68/79=86%) and cadaveric specimens for surgical approaches (63.79=80%).Conclusions: While all PGY-1 orthopaedic residents are now required to spend six months on orthopaedic rotations, the remaining six months are variable. These non-orthopaedic rotations are likely determined by the PD and available services at the trainee’s institution. This variability has granted PDs the opportunity to individualize the intern experience by maximizing each institution’s assets and designing their own surgical skill curriculum to train their interns using the resources available. The primary changes introduced more orthopaedic-specific rotations to minimize the time spent on general surgical services. Specifically, the new requirements include: six months of orthopaedic surgery, at least three months of general surgical rotations, and an additional three months of structured training in orthopaedic-related specialties . Orthopaedic residency programs must also include a surgical skills curriculum that addresses a list of 17 skills and competencies  and Accreditation Council for Graduate Medical Education (ACGME) instituted a redesigned PGY-1 curriculum.tencies .While all programs are required to institute these changes to the PGY-1 curriculum to maintain their accreditation, to our knowledge, no studies have examined the differences in implementation on an individual program level. The ACGME and ABOS created guidelines for modification to the intern year curriculum, however, orthopaedic residency program directors (PDs) are allowed to select from a specific set of non-orthopaedic rotations  that influence the training and overall quality of the experience for interns prior to commencement of their orthopaedic-specific training in the remaining four years. In addition, a standard surgical skills curriculum has not been defined; rather, orthopaedic residency programs have the opportunity to design a curriculum that meets the needs of their residents.The purpose of this study was to examine how the ACGME/ABOS guidelines were implemented on a national level. We hypothesized that there would be considerable variability in the non-orthopaedic rotations included in the intern year with regards to the amount of surgical  versus non-surgical  exposure provided. Additionally, we hypothesized that the structure of the surgical skills curriculum would vary among orthopaedic residency programs.After obtaining IRB approval (Protocol #5152), an anonymous survey was distributed to PDs for all ACGME-accredited orthopaedic surgery residency programs in the United States using SurveyMonkey . At the time of the survey (January 2017), there were 163 orthopaedic residency programs, 155 of which were civilian, and eight of which were military residency programs. Contact information for orthopaedic residency PDs was obtained from publicly-accessible data sources including FREIDA (Fellowship and Residency Electronic Interactive Database), ACGME program listings, and individual program websites. Two follow-up emails were sent, one at two weeks and another at four weeks, to encourage more participation. Participation was entirely voluntary.The survey contained multiple choice questions designed to gather program demographics including geographic location, university-based versus community-based program, size of each residency class, number of faculty members, and rotation length during the intern year. Additionally, the survey included questions specific to intern year, including identifying all non-orthopaedic rotations, the presence of an intern boot camp at the beginning of the year, and a formal surgical skills curriculum.Data was retrieved and analyzed using the SurveyMonkey web application. Descriptive statistical analysis was performed.Electronic surveys were sent to PDs at the 163 ACGME accredited orthopaedic residency programs in the U.S.; however, one survey was returned as undeliverable, leaving 162 programs in the study group. Seventy-nine of 162 PDs (49%) completed the survey in its entirety. Twenty (25%) of the respondents were at programs in the Northeast, 24 (30%) were in the Midwest, 23 (29%) were in the South, and 12 (15%) of the PDs were at residency programs in the West . Many ofThe residency PDs represented programs that varied in size from 0-2 residents per year to classes with more than 11 residents per year . Thirty-Sixty-one of 79 programs (77%) had 12 three-to-four week rotations covering the orthopaedic-related specialties, as well as non-orthopaedic surgical and clinical rotations throughout PGY-1. Thirteen programs (17%) had first-year rotations that lasted between five and eight weeks, while five programs (6%) had first-year rotations that were longer than eight weeks. The most common non-orthopaedic rotations included: general surgery trauma (67/79=85%), surgical/medical intensive care unit (60/79=76%), and plastic and burn surgery (56/79=71%) .Forty-six of 79 programs (58%) held an intern boot camp during the first two months of the academic year, which is separate from clinical rotations. The majority of these programs (27/46=57%) consisted of one-week sessions to train interns in basic surgical and orthopaedic skills.Seventy-two of 79 residency programs (91%) had a formal surgical skills curriculum for first-year residents, separate from intern boot camp. Nine of the 72 programs (13%) collaborated with other orthopaedic residency programs for the surgical skills curriculum. Forty-one of 72 programs (57%) utilized a year-long curriculum for the surgical skills training, while a dedicated rotation, separate from clinical responsibilities, was used by 31 programs (43%). Twenty-two of the 31 (71%) programs that utilized a dedicated block for surgical skills training had a four-week curriculum, while two-week (5/29=16%), and six-week (2/29=6%) schedules were less common.Many training modalities were employed to teach first-year residents the surgical skills outlined by the ABOS Surgical Skills Modules including cadavers to practice surgical approaches (63/79=80%) and saw bones to learn the basic skills necessary to perform internal fixation of fractures (68/79=86%) . When teThis study demonstrated substantial variability in the implementation of the ABOS and ACGME curricular requirements in orthopaedic residency programs throughout the United States. A few non-orthopaedic rotations  were included in the first-year curriculum for over half of the programs; however, the remaining rotations varied considerably between institutions. Roughly half of orthopaedic residency programs offer an intern boot camp during the first two months of PGY-1; however, most of the programs (91%) have a formal surgical skills curriculum for interns, separate from the intern boot camp. In designing surgical skills curricula, most programs include activities to augment didactic and self-directed study such as cadaver labs (80%) and saw bones (86%). There is wide variability in the use of arthroscopic simulation , with programs likely utilizing more than one modality. By increasing the orthopaedic surgery rotations from three- to six-months, first-year residents spend more time working directly with upper-level residents and attendings, providing the interns with increased exposure to both inpatient and outpatient clinics, as well as the operating room. In addition to changes to the rotation schedule, the 2013 modifications required programs to create basic surgical skills curricula designed around 17 modules at the discretion of the PD, utilizing the resources available to each residency program.Since 2013, the ABOS and ACGME have implemented major changes to the curricular requirements for first-year orthopaedic residents, including revisions to the PGY-1 rotation schedule. The authors concluded that both residents and faculty members found the initial iteration of the surgical skills curriculum to be an effective teaching model that could be improved with minor refinements from year to year. Ford et al. described the surgical skills curriculum designed to train orthopaedic interns at Carolinas Medical Center. The study described numerous details about the surgical training program including total cost  and time spent by the residents practicing the surgical skills (89 hours). Overall, the residents were satisfied with the structure of the curriculum, with the average module receiving 4.15 points out of 5 (4 represented “good” and 5 represented “excellent”). The authors also described the invaluable benefit of early intern-attending interactions, allowing for the development of clinical and research relationships during the first year of residency. A third study conducted at the University of Toronto demonstrated similar beneficial results of an intern boot camp after dividing the first-year residents into three groups - on-service, off-service, and intensive skills laboratory groups. The residents in the skills laboratory group performed significantly better than both residents on and off orthopaedic services. While the implementation of surgical skills curricula seems to be well-received by orthopaedic residents and faculty, the study was unable to quantify the effect, thereby stating that it is unclear if these programs lead to an overall improvement in surgical skills and a transfer of techniques learned in the laboratory to the operating room. In 2015, a study by Jones et al. compared scores in task-specific measures between PGY-1 residents following a three-month orthopaedic “intern boot camp” and PGY-2 residents immediately following their orthopaedic internship that did not include the surgical skills curriculum. The authors found that there was no difference in performance during the surgical skill examinations between the two groups.Numerous publications describe the initial experience with the design and implementation of a surgical skills curriculum into orthopaedic residency programs. Karam et al. detailed the experience at the University of Iowa, which created one of the first month-long surgical skills training programs for PGY-1 residents. A separate study demonstrated the improvement of diagnostic shoulder arthroscopy skills and competency after residents had completed Virtual Reality (VR) simulated training sessions. Another recent study detailed the current state of simulation training in orthopaedics and concluded that simulation is an effective training modality to improve technical skills. Furthermore, this study described a push to include an independent surgical skill evaluation during the orthopaedic surgery board certification process.In addition to examining the effect of an overarching surgical skills curriculum, there have been studies that examine the ability of cadaveric instruction and surgical simulators to aid in the instruction of surgical residents. A study by Van Heest et al. in 2009 evaluated the ability of orthopaedic surgery residents to complete a cadaveric carpal tunnel release. The authors found a significant difference between year of training and ability to adhere to a detailed surgical checklist. Second, this survey study is subject to the limitations that are inherent to this type of investigation, including failure to complete the survey by some respondents and varied interpretations of the questions. To address this limitation, the survey was designed such that all questions required a response, thereby preventing the respondent from skipping any questions. Additionally, all survey questions included multiple choice responses, thereby limiting the amount of individual interpretation by PDs.There are several limitations to this study. First, only seventy-nine of the 162 PDs (49%) responded, therefore, these results may not be generalizable to all of the orthopaedic residency programs in the United States. However, several previously published studies that surveyed orthopaedic residency PDs demonstrate similar response rates, varying from 16-56%.While all PGY-1 orthopaedic residents are now required to spend six months on orthopaedic rotations, the remaining six months of the intern schedule consist of non-orthopaedic rotations that are determined both by the residency PD and, likely, the services available at the trainee’s institution. This variability has granted PDs the opportunity to individualize the intern experience to maximize the assets of the given institution. Additionally, although the skills deemed necessary for a PGY-1 orthopaedic resident have been defined by the ABOS surgical skills modules, each residency program can design their own curriculum to train their interns using the resources available.Jeffrey D. Tompson is an orthopaedic surgery resident at Rutgers New Jersey Medical School.Jeffrey D. Trojan is a research assistant in the Department of Orthopaedic Surgery at Tulane University School of Medicine.Mary K. Mulcahey is an associate professor and the director of the Women’s Sports Medicine Program in the Department of Orthopaedic Surgery at Tulane University School of Medicine. This review has been migrated. The reviewer awarded 4 stars out of 5 An interesting and well written paper. As we move more and more to super-specialities, the "add-ons" that such such subjects as orthopeadic surgery become important. I imagine that frequently it is a difficult choice for programe directors and there becomes a balance between standardisation and interesting others. I think this is an important paper since it brings to the fore this discussion need. Personally I feel that there are surgical subjects that are closer to orthopeadic sugery than others and it should be these that control what other surgical subjects are includedReviewer Expertise:NANo decision status is available This review has been migrated. The reviewer awarded 3 stars out of 5 This paper will be of interest for those involved in training for orthopaedics and organisers of training programmes where a change on the programme has been mandated by their specialty and accrediting organisations. The survey demonstrates that within the parameters set in terms of learning experiences and outcomes, there is considerable flexibility in the organisation of of the training programmes. While this gives a useful baseline measurement, it would have been interesting to know how each training provider developed their new programmes. It is not clear whether these are based on availability of rotations and issues such as faculty for surgical skills boot camps, or if not, what criteria was used to design the programmes. The paper is well written and the demonstrated variation in organisation across the training programmes would be a good baseline for a further study to consider the experiences of the trainees in these differing programmes.Reviewer Expertise:NANo decision status is available


Recent advancements in functional near-infrared spectroscopy technology have offered a portable, wireless, wearable solution to measure the activity of the prefrontal cortex (PFC) in the human neuroscience field. This study is the first to validate the different contributions made by the PFC's eight subregions in healthy young adults to the reactive recovery responses following treadmill-induced unpredictable slip perturbations and vibrotactile cueing .Our fall-inducing technology platform equipped with a split-belt treadmill provided unpredictable slip perturbations to healthy young adults while walking at their self-selected walking speed. A portable, wireless, wearable, and multi-channel (48 channels) functional near-infrared spectroscopy system evaluated the activity of PFC's eight subregions  as quantified by oxyhemoglobin and deoxyhemoglobin concentrations. A motion capture system and two force plates beneath the split-belt treadmill were used to quantify participants' kinematic and kinetic behavior. All participants completed 6 trials: 2 consecutive trials without vibrotactile cueing and with a slip perturbation ; 3 trials with vibrotactile cueing [2 trials with the slip perturbation  and 1 trial without the slip perturbation ], and 1 trial without vibrotactile cueing and with a slip perturbation . The PFC subregions' activity and kinematic behavior were assessed during the three periods .Compared to the walkers' standing and walking periods, recovery periods showed significantly higher and lower levels of oxyhemoglobin and deoxyhemoglobin concentrations, respectively, in the right and left DLPFC, VLPFC, and FPFC, regardless of the presence of vibrotactile cueing. However, there was no significant difference in the right and left OFC between the three periods. Kinematic analyses confirmed that vibrotactile cueing significantly improved reactive recovery responses without requiring more involvement by the PFC subregions, which suggests that the sum of attentional resources is similar in cued and non-cued motor responses.The results could inform the design of wearable technologies that alert their users to the risks of falling and assist with the development of new gait perturbation paradigms that prompt reactive responses. Falls are a major global health concern in all populations, particularly the elderly  increased during balance recovery following unpredictable gait perturbations , a neuroimaging technique that offers several advantages over functional magnetic resonance imaging, electroencephalography, etc.   from the two force plates of the split-belt treadmill at a rate of 100 Hz.The customized control unit for vibrotactile cueing (C2 tactor) is a commonly used linear actuator with a moving contactor. The contactor, shielded within a passive housing, oscillates perpendicularly to the skin. Our custom software wirelessly sends a command signal to the control unit that generates the 250 Hz sinusoidal signal driving the C2 tactor. The peak-to-peak displacement amplitude of vibration is approximately 200 μm at the selected frequency  and to the fNIRS software via an Ethernet connection). It also sends event signals associated with the experimental protocols to both Nexus 1.8 and fNIRS software (see Section 2.3). The measured communication delay of the synchronization and event signals is <1 ms.2 ; and 1 trial without vibrotactile cueing and with a slip perturbation . The three trials with vibrotactile cueing were randomized. Based on our previous studies, we determined that six trials would eliminate the potential for learning effects  because stepping is a common recovery response , a walking period , and a post-perturbation period . The custom software increased the speed of the treadmill's two belts between the standing and walking periods and decreased it after the post-perturbation period at a rate of 0.2 m/sTo minimize head movements and side-to-side walking variations, participants walked on the split-belt treadmill at their self-selected walking speed while fixing their gaze on an “X” mark placed ~4.5 m ahead at eye level  processed the optical power, whole-body kinematics, and GRFs.2Hb) and a concomitant decrease in deoxyhemoglobin concentrations (ΔHbR)  to eliminate high-frequency instrumental and environmental noises based on the power spectral density analysis of the raw data. The application of a signal-to-noise ratio (SNR) of <30 dB rejected unreliable or distorted channels; SNR was defined as the ratio of a mean to a standard deviation of the fNIRS's filtered data for the baseline first 5 s of the recorded period (corresponding to one-third of the quiet standing period). The SNR threshold of 30 dB was chosen because it effectively extracted reliable ΔO2Hb and ΔHbR were computed by the modified Beer–Lambert law  relative to the baseline period for the 780-nm and 850-nm wavelengths were computed for the accepted channels .The Montreal Neurological Institute transformation was conducted by individual location coordinates in four positions . The post-hoc analysis showed that response latency was significantly shorter for the cueing and catch trials than for the control and post-control trials. The post-hoc multiple comparisons between the cueing and catch trials and the control and post-control trials were insignificant.post-hoc multiple comparisons. The post-hoc analysis showed that trunk AD, trunk ROM, and COM ROM were significantly higher during the recovery period than the standing and walking periods for the control, cueing, and post-control trials. The post-hoc analysis for the same trials also showed that the minimum COM position was significantly lower during the recovery period than for the standing and walking periods. Furthermore, a significant increase in the trunk AD, trunk ROM, and COM ROM and a significant decrease in the minimum COM position during the recovery period compared to the standing and walking periods resulted in a significant interaction (condition × period) effect.post-hoc multiple comparisons of trunk AD, trunk ROM, COM ROM, and minimum COM position showed insignificant differences between the walking and recovery periods. The post-hoc analysis also showed that trunk AD, trunk ROM, and COM ROM were significantly higher during the walking period than the standing period regardless of the trial condition, and that the minimum COM position was significantly lower during the walking period than the standing period regardless of the trial condition.For only the catch trial, the post-hoc analysis showed that the catch trial had the smallest trunk AD, trunk ROM, and COM ROM and the largest minimum COM position compared to the other trials. The same analysis also showed that the cueing trial had the second smallest trunk AD, trunk ROM, and COM ROM and the second lowest minimum COM position compared to the other trials. The post-hoc multiple comparisons of trunk AD, trunk ROM, COM ROM, and minimum COM position between the control and post-control trials were insignificant, which indicated no learning effect by repetition.For only the recovery period, the F (3.36) = 12.470, p < 0.0001]. post-hoc multiple comparisons.The one-way ANOVA applied to the step response time showed a significant main effect of the trial condition [post-hoc analysis showed that the step response time during the cueing and catch trials was significantly shorter compared to the control and post-control trials. The same analysis showed that the cueing and catch trials had the smallest and second smallest step response times, respectively. The post-hoc multiple comparisons between the control and post-control trials were insignificant, which indicated no learning effect from repetition. The step response time (0.52 ± 0.05 s) of the catch trial was similar to the average right step time (0.54 ± 0.05 s) during the walking period of the catch trial.The This study found differences in the contributions of the PFC's eight subregions to the reactive recovery responses following unpredictable slip perturbations, walking on a treadmill, and processing vibrotactile cueing. Notably, vibrotactile cueing improved reactive recovery responses compared to the control and post-control trials without further increases in PFC activity.Previous studies using fNIRS have found increases in PFC activity during balance recovery following external perturbations  while standing ; and no measurement of systemic physiological changes. Future research will add measurement devices to record systemic variables  (Tachtsidis and Scholkmann, Regardless of the presence of vibrotactile cueing, bilateral DLPFC, VLPFC, and FPFC activities substantially increased during the recovery period following unpredictable slip perturbations. Vibrotactile cueing significantly improved kinematic behavior with no further increases in PFC activity during the recovery period and confirmed the beneficial effects of precues on reactive recovery responses following unpredictable slip perturbations. Without the slip perturbation, vibrotactile cueing also increased bilateral DLPFC, VLPFC, and FPFC activities, but the increased activity was significantly less than the activity in the control, cueing, and post-control trials with and without vibrotactile cueing. While vibrotactile cueing will provide users with navigational guidance to avoid upcoming hazards, longer cueing durations or more complex coding schemes are likely to require more attentional resources for interpretation. We believe that our findings can improve the development of fall reduction and prevention technologies that have vibrotactile cueing alerts.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.The studies involving humans were approved by Institutional Review Boards of the University of Houston. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.B-CL conceived the study, designed the experimental protocols, supervised data collection, performed data and statistical analysis, interpreted the results, and drafted the manuscript. JC performed data analysis and drafted the manuscript. JA assisted with data interpretation and manuscript preparation. BM assisted with designing the experimental protocols, interpreted the results, and drafted the manuscript. All authors contributed to the article and approved the submitted version.


Training in the basic interview skills of clinical history-taking has always been a significant component of medical education.This study was designed to identify the factors influence medical students’ history-taking skills learning and develop a way to improve these skills.We firstly analysed the academic performance of medical students at Jinan University School of Medicine in different disciplines of the Clinical Medicine Level Test (CMLT), to ensure the students have obtained comprehensive medical education prior to beginning their clinical internships. Next, we conducted a survey among the CMLT participants to seek the underlying causes and corresponding measures to improve history-taking in the future. Before these medical students entered their fifth-year clinical practice, we finally provide them with pre-internship training, including the history-taking workshops with standard patients (SP).The analysis of the clinical skill sections of the CMLT revealed that the students performed significantly better on clinical operations from multiple disciplines than on medical history-taking. Principal component analysis of the survey questionnaire indicated that the capability of history-taking, course assessments, and awareness of the value of medical history-taking emerged as the key factors forming a cohesive clue for sustaining history-taking implementation. The intervention workshops of employing SP had a positive impact, as evidenced by the students’ feedback and suggestions for improving their ability of history-taking.This study suggests that strengthening of medical history-taking training is indispensable for training qualified medical students. Workshops with SP is a successful teaching strategy for practicing history-taking, allowing students to spot minute errors and training communication skills. As a certified physician, the ability to gather an accurate medical history through patient interviews is an essential skill. The process of eliciting relevant personal, psychosocial, and symptom information from a patient is defined as “history-taking”, which contributes to obtaining useful information in formulating a diagnosis and providing medical care to the patient . Despitein vivo demonstration. As a result, the objective structured clinical examination (OSCE), an assessment designed to measure the performance of medical tasks in a high-fidelity way, has been extensively employed to evaluate the effectiveness of medical students’ history-taking and communication skills  testing both the integrated clinical encounter (ICE) and communication and interpersonal skills (CIS) within the Step 2 Clinical Skills exam (CS) . Howevern skills . OSCE walls  system has been developed in many countries to control the quality of newly licensed physicians in everyday medical practice . In ChinThrough analyzing the medical students’ CMLT scores and collecting their feedback, this study has the following purposes: 1. Identifying the gaps between our current teaching approaches and development of medical students’ clinical abilities; 2. Establishing some post-intervention practice to cover the gaps; and 3. Improving the quality of medical students training continuously. The problem focused in this study is the deficiencies in medical history-taking training identified by CMLT score analyzing, and subsequent corrective interventions.In total, 168 students at Jinan University School of Medicine attended the CMLT. These participants were fourth-year undergraduates in clinical medicine who were enrolled in 2017. The examinees were 91 (54.17%) male and 77 (45.83%) female students; the average age was 22.42  ± 1.18 years old; 129 (76.79%) students were from mainland China and 39 (23.21%) were from overseas; 147 (87.50%) students studied medicine in Chinese, and 21 (12.50%) students studied medicine in English. In the spring semester of 2021, the CMLT was administered to medical students who were in the final year of their studies, prior to their internships. The examination included both written and OSCE components, with six stations covering medical history-taking, physical examinations, cardiopulmonary resuscitation, blood collection by venipuncture, and surgical suturing . The resAfter analyzing the CMLT scores, each participant was requested to complete a questionnaire on SoJump , which is an online survey platform in mainland China, aimed at collecting medical students’ learning experiences on history-taking before the CMLT. Additionally, the questionnaire aimed to gather the undergraduates’ feedback and attitudes towards history-taking. The survey included a total of 16 items, with three related to demographic information and 13 about medical students’ learning experiences before the CMLT. Participants were required to rate their experience using a 5-point Likert scale, with the range of “1 = strongly disagree” to “5 = strongly agree”. The last two items of the survey inquired about the medical students’ preference and training methods regarding history-taking. To ensure that the questionnaire was well-received by Chinese medical students, it was created in Chinese  What do you believe is the most important aspect of medical history-taking? (2) What do you consider the most effective way to master the skills of medical history-taking? (3) What kinds of teaching methods are more helpful to your studies? Participation in the survey and interviews was voluntary, and all respondents were informed of the study’s purpose and procedures. They were provided with written consent forms and informed that they could withdraw at any time. To maintain confidentiality, the materials were de-identified in the transcripts, and the data were only accessible to the authors. This study was conducted in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of Jinan University (No. JNUKY-2021-039).t test (2-tailed) was used to compare (1) the average OSCE scores of four different subjects and the average 6-station OSCE score of all the participants; and (2) the average score of individual test contained in each OSCE subject and the average score of each OSCE subject. Paired samples t test was used to compare the average scores for evaluating the medical students’ history-taking and clinical operation skills of internal medicine in OSCE. The data obtained from the questionnaires were analyzed using Cronbach’s alpha test to determine the internal consistency of the responses. Factor analysis  was employed as a useful tool for characterizing and quantifying the influencing factors of the students’ history-taking skills . As a result, the average standard score of the 168 OSCE participants is 50. Four subjects classified by discipline were statistically examined . The desTo further validate the preliminary analysis of the results mentioned above, we compared the average score of each test from the 168 participants with the overall average scores of each subject, including history-taking, surgical operation and emergency operation. The results showed that the most significant difference occurred in the items related to history-taking, whereas there were a few significant differences in either surgical or emergency operations .We then proceeded to compare the OSCE scores between history-taking and general hospital clinical operation of internal medicine. The results indicated that the average score for history-taking was significantly lower than that of general hospital clinical operation .α of the 11 items on the participants’ acknowledgement and assessments about medical history-taking was 0.680, indicating a good reliability of the survey tool (To explore the key factors influencing students’ performance in medical history-taking, we administered a survey questionnaire. All the 168 CMLT participants completed the questionnaire. The Cronbach’s vey tool . The privey tool . Other tvey tool .Based on the deficiencies in history-taking revealed by the CMLT, we implemented a series of remedial measures, which included organizing workshops on history-taking during a 4-day pre-internship training program, as a specific form of improvement. In the targeted training, we took into consideration the students’ learning preference, and employed SP to introduce the procedure of history-taking and gave the students deliberate practice. The SP interviewing scenarios were recorded and reviewed with feedback and discussion session facilitated by either group members or the teacher. Throughout the review process, some subtle issues in the beginning of the interview, problem-solving, communication, and summary were perceived, until a more standardized structure for history-taking was established. The SP interviews in the workshop were supplemented by mini-lectures, small group exercises such as role-play and self-reflection.After the pre-internship training, 20 students were interviewed to assess the effectiveness of these training modules. Prior to internships in China, the CMLT evaluates the effectiveness of teaching and the learning outcomes of medical students. Although not yet mandatory for all Chinese medical students, accumulated experience in recent years has shown that it is beneficial in increasing the practitioners’ NMLE passing rate .This study initially compared the CMLT performance of several groups of medical student cohorts at Jinan University School of Medicine in 2021. The primary conclusion of the analysis was that clinical history-taking had poor performance, indicating that there may be inherent or external factors affecting the learning outcomes of medical students. Subsequently, we focused on the causes of medical students’ unsatisfactory performance in taking patients histories. We conducted an analysis of the specific variation to provide useful information for enhancing the effectiveness of history-taking instruction.In recent decades, medical history-taking has been prioritized in clinical medical education, with numerous medical schools developing consensus guidelines emphasizing its significance . ClinicaOn the other hand, the students were dissatisfied with the current teaching approaches for medical history-taking, and they wished for more opportunities to contact actual patients or be trained with SPs that could mimic clinical scenarios while reducing the time for classroom instruction on history-taking . This atetc (Regarding the improvement of medical students’ history-taking skills, Keifenheim et al. suggested several educational interventions. These include implementing small group workshops that involve role-playing and interviews with real patients, discussing the most common and best cases among the participants, and promoting instructive experiences and lessons through videotape reviews etc . In lighetc . This fietc . The reaThis study has several practice implications:1. Communication skills for medical interviews should be emphasized through effective training methods.2. SP training for practicing history-taking can be incorporated into the routine clinical training curriculum.3. Simulative learning environments that can replicate every step of history-taking and allow students to spot minute errors are a successful teaching strategy.The present study has both strengths and limitations. The first limitation is that the conclusions were derived from one CMLT and the subsequent survey at Jinan University School of Medicine, so they may not be completely applicable to all teaching hospitals. There are numerous different teaching facilities and instructional strategies that could influence the perceptions of medical students regarding the advantages and disadvantages of medical education. Second, while we intended for the CMLT to reflect the educational situation of basic and clinical medicine and provide a beneficial supplement for the formal examination of doctors’ qualifications, there may be flaws in the structure, design and practical experience due to the limited time and scope of implementation.10.7717/peerj.15052/supp-1Supplemental Information 1Click here for additional data file.10.7717/peerj.15052/supp-2Supplemental Information 2Click here for additional data file.10.7717/peerj.15052/supp-3Data S1Click here for additional data file.


Understanding human genetic influences on the gut microbiota helps elucidate the mechanisms by which genetics may influence health outcomes. Typical microbiome genome-wide association studies (GWAS) marginally assess the association between individual genetic variants and individual microbial taxa. We propose a novel approach, the covariate-adjusted kernel RV (KRV) framework, to map genetic variants associated with microbiome beta-diversity, which focuses on overall shifts in the microbiota. The KRV framework evaluates the association between genetics and microbes by comparing similarity in genetic profiles, based on groups of variants at the gene level, to similarity in microbiome profiles, based on the overall microbiome composition, across all pairs of individuals. By reducing the multiple-testing burden and capturing intrinsic structure within the genetic and microbiome data, the KRV framework has the potential of improving statistical power in microbiome GWAS.IL23R, reported in a previous microbiome genetic association study and discovered 3 other novel genes, 2 of which are involved in immune functions or autoimmune disorders. In addition, simulation studies show that the covariate-adjusted KRV has a greater power than other microbiome GWAS methods that rely on univariate microbiome phenotypes across a range of scenarios.We apply the covariate-adjusted KRV to the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) in a two-stage  genome-wide association analysis for gut microbiome beta-diversity. We have identified an immunity-related gene, Our findings highlight the value of the covariate-adjusted KRV as a powerful microbiome GWAS approach and support an important role of immunity-related genes in shaping the gut microbiome composition.Video AbstractThe online version contains supplementary material available at 10.1186/s40168-023-01530-0. Bifidobacterium, a genus of beneficial gut bacteria that utilizes lactose as an energy source, has been associated with a non-persistence genotype of the human lactase gene (LCT), which typically results in lactose intolerance [The human microbiome plays an important role in host health and is involved in fundamental body functions such as metabolism and immune response , 47. Whiolerance , 26, 38.Many studies have sought to identify genetic variants that influence microbial composition, and most of them incorporate microbiome characteristics as phenotypes in genome-wide association studies (GWAS). Typical analyses marginally test the association between abundances of individual taxa and genotypes of individual genetic variants , 33, 38.As the microbiome functions as a community, an alternative microbiome phenotype is beta-diversity, the dissimilarity in overall microbiome profiles between individuals. Beta-diversity analysis represents a standard mode of analysis in microbiome profiling studies as it focuses on discovery of concerted shifts in the community rather than individual taxa. However, few studies have considered beta-diversity as a trait of interest in microbiome GWAS and there is no standard strategy. Some studies , 62 haveHere, we propose to assess the association between groups of variants at the gene level and the overall microbiome composition, characterized by beta-diversity, at the community level. Community-level analyses and multi-variant testing have been shown to be powerful in microbiome , 70 and Although the KRV is a potentially powerful approach for microbiome GWAS, the KRV framework lacks a general strategy to control for covariates such as population structure, which is imperative for any genetic association analysis. Here we extend the original KRV framework to allow for flexible covariate adjustment.IL23R) reported in a previous microbiome genetic association study and discovered other novel genes related to immune functions. Furthermore, we have identified individual genetic variants and specific microbial taxa involved in these gene-microbiome associations. In addition, our simulation results show that the covariate-adjusted KRV maintains valid type I error rates in the presence of confounding and has a much greater power than other single-trait-based competing methods across a range of scenarios. Together, our proposed approach demonstrates good statistical properties and provides a powerful way to study the effect of human genetic variation on microbiome composition.We apply the covariate-adjusted KRV to the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) , 60 via We aim to assess the covariate-adjusted association between genotypes of multiple genetic variants within a gene and abundances of microbial taxa at the community level, using the previously developed KRV framework. We now give an overview of the original KRV framework and extend it to allow for flexible covariate adjustment. The overall procedure for covariate-adjusted KRV in the context of microbiome GWAS is shown in Fig. G, and a group of traits, Y. Suppose we have genotype data of m genetic variants and phenotype data of q traits available for n unrelated individuals. For the i-th subject, let l-th variant; let m genetic variants within a particular gene, and q microbial taxa that form the microbiota.The KRV framework has been proposed by Zhan et al. , 69 to e pathway . In the i and j. Let i and j. Specific choices of kernel functions in the context of microbiome GWAS are discussed in Methods: i, j)-th entry of Let p-value and assess the significance of the association at a given significance level.Intuitively, the KRV coefficient compares genotypic similarity to phenotypic similarity across all pairs of individuals. A large KRV coefficient indicates that the pairwise similarity pattern in genetic profiles well resembles the pairwise similarity pattern in phenotypic profiles, which implies that the genetic variants are associated with the traits in a certain way. To perform hypothesis testing, the permutation distribution of the KRV statistic under the null hypothesis of no association between genetics and phenotypes can be approximated by a Pearson Type III distribution , allowini, we have a set of covariates i-th row of The above framework does not take into account any covariates that might be involved in a typical genetic association study. Now suppose that, for each individual approach , 69, wheTo adjust for covariates in a general way, we propose a novel adjustment approach that applies to all possible kernel types, regardless of the requirement for input data. Our approach is based on kernel principal component analysis (kernel PCA) , a genermentclass2pt{minimp-value. In this case, the null hypothesis is that there is no association between the genetics and the phenotypes after adjusting for the effects of the covariates.The usual hypothesis testing procedure in the KRV framework can be applied to the adjusted KRV statistic to obtain a In the KRV framework, kernel functions are used to summarize pairwise similarities in genotype and phenotype profiles among the subjects. In order to improve the statistical power in hypothesis testing, we would like to choose kernels that better reflect the actual structure within the genetic and phenotype data as well as the patterns of association , 70. ForFor genotype data, popular kernel functions include the linear kernel variants . Dependivariants .For microbiome data at the community level, the kernel matrix can be obtained by transforming known ecological or phylogenetic dissimilarity measures . For example, Bray-Curtis dissimilarity quantifies the dissimilarity between two microbial communities based on the difference in counts at each taxon between the two communities. The UniFrac distances are dissimilarity measures based on the phylogenetic structure of the taxa , 45, 46:While the Bray-Curtis dissimilarity and UniFrac distances take scaled or rarefied microbial counts or presence/absence information as input, microbial dissimilarity can also be calculated from other types of transformed abundance data. For example, the centered log-ratio (CLR) transformation , 24 and Given a pairwise dissimilarity matrix  package , where wWe note that taking Euclidean distances followed by kernel matrix transformation is equivalent to constructing a linear kernel matrix based on the same data  is a community-based prospective cohort study aimed to identify risk factors for health outcomes in Hispanic/Latino populations in the USA. The study recruited 16,415 Hispanic/Latino adults aged 18–74 years, representing diverse ethnic background, at four US field centers , using a two-stage probability sampling design .N is the sample size and v is the ratio of observed variance of imputed dosages to the expected binomial variance [12,803 participants consented to genetic studies. Genotyping was performed on an Illumina custom array, SOL HCHS Custom 15041502 B3, which consisted of the Illumina Omni 2.5M array (HumanOmni2.5-8v1-1) and As an ancillary study, the HCHS/SOL Gut Origins of Latino Diabetes (GOLD) study was further conducted to investigate the role of gut microbiome composition in diabetes and other health outcomes in Hispanic/Latino individuals . Gut micThe HCHS/SOL study was approved by the Institutional Review Boards of all participating institutions, and written informed consent was obtained from all participants.To identify genetic variants associated with the overall gut microbiome composition in Hispanic/Latino individuals, we applied the covariate-adjusted KRV test to the HCHS/SOL study in a genome-wide association analysis for gut microbiome beta-diversity.We considered genetic variants  within For each gene, we assessed the association between common variants  kernel PCs derived from the kernel matrices, as mentioned in Methods: Our investigation of the genetic effect on the microbiome involved two stages. In the first stage, we tested the association between the variants in each gene and the microbiome profile at the community level. In the second stage, for any genes called significant in the first stage, we marginally assessed the association between each of the individual variants within those genes and the community-level microbiome profile to look for significant variants, again using the covariate-adjusted KRV. Bonferroni correction was applied in both stages. Since this was a nested hypothesis testing approach, the second-stage test only required correction for the number of variants in the genes that were called significant in the first stage. All analyses were performed on unrelated individuals  , a kernementclass2pt{minimWe conducted simulation studies to further evaluate the type I error rate and power of the covariate-adjusted KRV test. We simulated genotype data and microbial OTU count data under realistic settings, and introduced population stratification as a confounder that affected both genetic and microbiome data.cosi2 program [The general simulation setting is as following. We considered a sample size of 1000. SNP genotype data over a 1-Mb chromosome were simulated for 500 individuals of African ancestry and 500 individuals of European ancestry. Specifically, we first generated 10,000 haplotypes of African ancestry and another 10,000 haplotypes of European ancestry over a 1-Mb chromosome according to coalescent theory using the  program . To formWe used a Dirichlet-multinomial distribution to generate microbial OTU counts for each individual in the sample, as this distribution well accommodates the over-dispersion of microbiome count data , 70. To Both unadjusted and adjusted KRV tests were performed to test the association between the overall microbiome composition (composed of 856 OTUs) and common SNPs . In Type I Error Scenario 1, we increased the abundance of the 10 most common OTUs by 10% in African individuals and then rarefied the abundance back to 1000 total counts per individual. In Type I Error Scenario 2, we increased the abundance of 10 rare OTUs (chosen randomly from the top 40 rarest OTUs) in African individuals by adding a unit count before rarefying the abundance back to 1000 total counts per individual. These two scenarios were not meant to reflect the microbiome difference between African and European individuals in reality, but they served as hypothetical situations to introduce confounding effect into the genetics-microbiome relationship. Here we used the estimated mean proportion parameters of the Dirichlet-multinomial distribution as a measure of OTU prevalence. 10,000 simulations were performed for each type I error scenario.i at a chosen common SNP. In Power Scenario 1, for each individual i, we increased the counts of the 11th–20th most common OTUs by a factor of i, where i, we increased the counts of 5 rare OTUs (chosen randomly from the top 40 rarest OTUs) by an addition of To evaluate the power of the covariate-adjusted KRV, we based our simulation setting on Type I Error Scenario 1 and further introduced genetic effect on the microbiome in three different power scenarios, where a single SNP affected the abundance of multiple microbial OTUs . Let 856 OTUs , we incrIn the power simulation, we also considered two competing methods that analyze the association between a group of variants and the overall microbiome composition but rely on univariate microbiome phenotypes, as described in Methods: We estimated the computation time of the covariate-adjusted KRV test for different sample sizes. For each sample size, we simulated 10 data sets and reported the average computation time. Given constructed genotype and microbiome kernel matrices and 10 covariates, the average computation times are 0.09, 1.23, 12.58, and 97.57 s on a laptop (2.7 GHz CPU and 16 GB memory) for sample sizes of 200, 500, 1000, and 2000, respectively. The gene-level analysis of the HCHS/SOL data set  took approximately 8 hours on a high-performance computing cluster , with computing jobs divided by chromosome.p-value QQ-plots of the first-stage gene-level analysis results. For all microbiome kernels, the unadjusted KRV produces highly anti-conservative p-values (with large genomic inflation factors), while the PC-adjusted KRV has well-controlled type I error rates  where additional covariates  are available and adjusted, IL23R and C1orf141 are no longer genome-widely significant  and the order of magnitude of their p-values (Table nt Table . Similarmentclass2pt{minimIL23R is of considerable interest: it encodes one part of the receptor for interleukin-23 (IL-23), a pro-inflammatory cytokine closely involved in autoimmunity [IL23R gene has been associated with inflammatory bowel diseases (IBD) including Crohn’s disease and ulcerative colitis [IL23R gene (rs11209026) was associated with a higher microbiome diversity and richness and a higher abundance of beneficial gut bacteria in the ileum of healthy individuals, suggesting the influence of host genetics on the microbiome prior to onset of IBD. In addition, a mouse-based experimental study [IL23R expression had altered gut microbiota and were susceptible to colonic inflammation, where increased disturbance of gut microbiota exacerbated the disease activity. Coupled with these results, our finding further supports that the gut microbiome may mediate the host genetic effect on the development of inflammatory diseases like IBD. In its normal function, the IL23R gene likely helps shape the overall gut microbiota towards a healthy composition, which may in turn support normal immune activities and prevent gut inflammation.Among these genes, immunity . The IL2 colitis , 58. In  colitis , the proR gene rs1209026 wC1orf141 gene, with uncharacterized protein function, has overlapping regions with IL23R. Variants in the IL23R-C1orf141 region have been associated with susceptibility to Vogt-Koyanagi-Harada disease, a multi-system autoimmune disorder that affects pigmented tissues, in Chinese and Japanese populations [ZFR gene encodes the highly conserved zinc finger RNA-binding protein, which is shown to prevent excessive type I interferon activation by regulating alternative pre-mRNA splicing [MTMR12 gene encodes an adapter protein for myotubularin-related phosphatases and is likely involved in skeletal muscle functions [The other genes are also interesting to further explore. The ulations , 54. Thesplicing . Preventunctions . OverallMTMR12 is more significant with the unweighted UniFrac kernel than with the CLR-linear kernel, we focus on unweighted UniFrac for our subsequent analysis of MTMR12. Figure IL23R and C1orf141 genes were combined into a single IL23R-C1orf141 region due to overlapping variants. Based on the analysis using the Bray-Curtis kernel, there are 72 significant variants (out of 557 common variants) in the IL23R-C1orf141 region (ZFR and 125 significant variants (out of 174 common variants) in MTMR12  variant from each identified gene. This is similar to a PCoA analysis. Figure R12 Fig. .Fig. 4PCTo further understand how the discovered genes drive differences in gut microbiome composition, we conduct an exploratory analysis to identify specific microbial taxa involved in the microbiome GWAS associations. Our strategy is to perform dimension reduction on both genetic and microbiome data and use correlation analyses to complement and help interpret our community-level analysis results.p-value < 0.05 from linear regression): these kernel PCs represent the microbial community profiles that mainly drive the gene-microbiome associations. In Step 2, we inspect genus-level microbial abundance data and identify taxa that contribute the most to the significant kernel PCs from Step 1  of the top variant, rs10789226, from IL23R is positively associated with the abundance of Bacteroides and Blautia, while being negatively associated with the abundance of Prevotella. Bacteroides and Prevotella are the most abundant genera in this study  and dominate the first PC of the Bray-Curtis kernel. These two genera have been studied extensively as metrics for dietary patterns [Prevotella-to-Bacteroides ratio is associated with greater obesity in Hispanic/Latino populations based on a previous study using HCHS/SOL data [Bacteroides compared to healthy individuals, although mixed roles of Bacteroides have been reported in other studies [Prevotella species are classically considered as commensal bacteria, increased abundance of certain Prevotella strains has been associated with mucosal inflammation and linked to chronic inflammatory diseases [The microbial taxa identified for each gene-microbiome association signal are listed in Table patterns , 27. IntSOL data . In termSOL data  suggests studies . On the diseases . Based oZFR and the unweighted UniFrac kernel. Allele T (vs. Allele A) of the top variant, rs2113093, from ZFR is positively associated with the abundance of two unidentified genera from Clostridiales and Ruminococcaceae. As Ruminococcaceae is an order that belongs to the Clostridiales family, this result is consistent with the strength of the unweighted UniFrac kernel in utilizing phylogenetic information. Ruminococcaceae helps maintain the gut health by producing short-chain fatty acids (SCFAs) [Ruminococcaceae has been associated with IBD disorders [Clostridiales strains have been shown to mediate effective immune response against colorectal cancer in mouse models [Clostridiales and Ruminococcaceae bacteria in mediating the effect of ZFR in regulating innate immune response, and Allele T of rs2113093 is likely associated with a more favorable gut microbiome composition.We next look at the taxa involved in the association between  (SCFAs) , and a disorders  and inflisorders . On the e models . These fOverall, the above findings offer us a better understanding of the identified community-level associations. Nevertheless, due to heterogeneity in functions of individual bacterial species and strains, a higher study resolution will be required to further elucidate the mechanisms underlying the association between the identified genes and the gut microbiome.As a comparison to our proposed covariate-adjusted KRV approach, we applied additional competing methods of microbiome GWAS to the same set of HCHS/SOL data , the CLR-linear kernel  and the PhILR-linear kernel , but not significant at the genome-wide level.At a study-wide significance level  based on various microbiome kernels: BANK1 , MAST3 , POMC (CLR-linear), C1orf21 (CLR-linear) and AHSA2 (PhILR-linear). Among these genes, POMC produces peptides involved in anti-inflammatory actions [BANK1 is associated with systemic lupus erythematosus [MAST3 and AHSA2 are associated with IBD [We next investigate the replication of signals found by previous gut microbiome GWAS studies in our analysis. We have examined the significance of 63 previously reported genes that harbor variants associated with gut microbiome beta-diversity , 62, 64  actions , BANK1 iematosus , and MASwith IBD , 66, corWe have conducted simulation studies to further evaluate the performance of our proposed covariate-adjusted KRV test in terms of type I error rate and power. Table Under Type I Error Scenario 2 Table , where pFigure Under large effect sizes Fig. , while tGiven the importance of the microbiome in human health, there is an emerging interest in studying the relationship between host genetic variation and human microbiome. Our methodological contribution in this work is twofold. First, we have proposed a novel microbiome GWAS approach to evaluate the association between gene-level genetic variation and community-level microbiome composition. Second, we have proposed a novel multivariate statistic, the covariate-adjusted KRV, to implement this approach with flexible covariate adjustment. By reducing the multiple-testing burden and aggregating small effect sizes between the genetics and the microbiome, our proposed approach improves statistical power and thus requires fewer samples to detect associations compared to the traditional marginal testing approach. Simulation studies show that the covariate-adjusted KRV maintains valid type I error rates in the presence of confounders and has a much higher power compared to other microbiome GWAS methods that rely on univariate microbiome phenotypes. In a genome-wide analysis of the HCHS/SOL data, we have identified four genes associated with gut microbiome beta-diversity. We have also identified individual variants within these genes and specific microbial taxa involved in the associations, which will be useful for future investigation of the mechanisms underlying the genetics-microbiome relationships.IL23R gene is especially interesting for future study, due to its recognition in previous microbiome genetic association studies [Most of the identified genes based on the HCHS/SOL data have been previously implicated in immune functions or immunity-related disorders. This is consistent with the works by Blekhman et al.  and Rühl studies  and its  studies , 34. Fur studies , 50, and studies  in patieIL23R-C1orf141 region, identified using Bray-Curtis, mainly associate with abundances of Bacteroides and Prevotella  in a reduced sample revealed similar results. However, the signal from the LCT locus and Bifidobacterium abundance at a study-wide significance in the taxon-level analysis, the LCT gene was not genome-widely significant in the community-level analysis. Bifidobacterium was a relatively common genus  in the HCHS/SOL data. However, when we analyzed the microbiome as a whole and used microbiome kernels that are efficient in detecting abundance changes in common taxa, such as Bray-Curtis and weighted UniFrac, abundance differences in Bifidobacterium were likely overshadowed by those in the most abundant genera such as Bacteroides and Prevotella. This discrepancy in results reflects the inherent difference between taxon-level and community-level analyses. On the other hand, none of the genes identified in our community-level analysis was replicated in the taxon-level analysis, highlighting the value of our proposed approach in discovering gene-microbiome associations that involve concerted shifts in the microbial community. Nevertheless, our proposed KRV framework is not meant to replace the existing taxon-level microbiome GWAS approaches, as the two modes of analysis focus on distinct types of genetic features. If one is interested in identifying both loci associated with individual taxa and loci associated with the overall microbiome composition, our proposed framework can be applied in conjunction with existing taxon-level GWAS approaches to provide comprehensive results.We have compared our gene-based community-level analysis to a traditional variant-based taxon-level microbiome GWAS conducted on the same data. While we identified an association between the We have also investigated the replication of signals from previous gut microbiome GWAS studies. Five previously reported beta-diversity-associated genes  have beeWhile we have focused on the application of our proposed approach to microbiome GWAS in this work, the covariate-adjusted KRV can also be applied to investigate the relationships among other types of multivariate omics data. For example, we can investigate microbiome-metabolome relationships by examining the association between microbiome composition and groups of host metabolites that belong to distinct metabolic pathways. Such an analysis was described in one of our previous works , where wWe have proposed a promising approach, the covariate-adjusted KRV framework, to study the covariate-adjusted association between host genetic variation and community-level microbiome composition, which demonstrates good performances in both simulations and real data analysis. The genes and loci identified using our approach will help elucidate the complex interactions among host genetics, gut microbiome and host immune systems. With the increasing collection of various omics data and high-dimensional traits, we expect the covariate-adjusted KRV to bring more discoveries by taking advantage of the innate structure within the omics and phenotypic data.Additional file 1. A PDF file that includes additional methods and results (Section S1-S3), supplemental figures  and short tables (Table S1-S2).Additional file 2. An XLSX file that includes supplemental long tables (Table S3-S5).


While there were challenges in the production areas, the observed COVID-19 control measures were generally implemented well in the non-production areas. Sixty surface samples from all areas were tested for SARS-CoV-2 RNA and 11.7% were positive. Multi-layered measures, informed by a workplace specific risk assessment, are required to prevent and control workplace outbreaks of COVID-19 or other similar respiratory infectious diseases.The meat-processing industry had frequent COVID-19 outbreaks reported worldwide. In May 2021, a large meat-processing plant in the UK had an outbreak affecting 4.1% (63/1541) of workers. A rapid on-site investigation was conducted to understand the virus transmission risk factors and control measures. This included observational assessments of work activities, control measures, real-time environmental measurements and surface microbial sampling. The production night-shift attack rate  was nearly five times higher than the production day-shift . Shared work transport was provided to 150 staff per dayshift and 104 per nightshift. Production areas were noisy (≥80 dB(A)) and physical distancing was difficult to maintain. Face visors were mandatory, additional face coverings were required for some activities but not always worn. The refrigeration system continuously recirculated chilled air. In some areas, the mean temperature was as low as 4.5 °C and mean relative humidity (RH) was as high as 96%. The adequacy of ventilation in the production areas could not be assessed reliably using CO Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmissible virus that has caused a pandemic of coronavirus disease COVID-19). SARS-CoV-2 virus can spread directly or indirectly from person to person primarily through respiratory droplets and aerosols, and can be spread by asymptomatic, pre-symptomatic and symptomatic individuals 9. SARS-C,6,7,8,9,Combinations of factors are likely to contribute to the frequency of workplace outbreaks in the meat-processing sector. Some of these are unique to the meat-processing sector, including a high density of workers and environmental conditions that may favour virus transmission, such as recirculating chilled air, lack of outside fresh air and low temperatures. Some studies also investigated the potential contribution of social inequalities in this sector, including foreign-born workers, employment contract type and shared accommodation and work commute . AlthougThis study describes an investigation, as part of the COVID-OUT (COVID-19 Outbreak Investigation to Understand Transmission) study , of an oThis outbreak investigation in a large meat-processing plant was part of the COVID-OUT study that involved on-the-ground investigations of twelve COVID-19 outbreaks in a range of workplace settings including manufacturing ,18, wareThe COVID-OUT study protocol was designed using a set of relevant World Health Organization (WHO) COVID-19 early investigation protocols ,22,23,24The protocol was applied consistently to the COVID-OUT study across multiple outbreak sites, including this investigation at a meat-processing plant. The methods are described in more detail as follows.A system was implemented where suitable outbreak sites were identified and notified to the study team by Public Health England  on 1 October 2021), the Health and Safety Executive (HSE), local authorities or individual organisations. Upon notification, the research team would rapidly approach and recruit companies that were experiencing outbreaks. With the employers’ informed consent, the research team would visit the outbreak site as early as feasible to collect relevant data. Participation in the study was voluntary. The COVID-OUT study was approved by the NHS North East Research Ethics Committee (Reference 20/NE/0282).On 9 June 2021, a workplace outbreak of COVID-19 was reported to the COVID-OUT study team. The outbreak was located in a large secondary meat-processing plant in England that processes  and dispatches over 1.5 million meat products per week for food retail. The company provided informed consent for the environmental assessment part of the study. This included allowing the research team access to the workplace to assess the physical environment, work practices and COVID-19 control measures; to conduct surface microbial sampling; and to access and analyse anonymised data relevant to this research study. The data included information on the workforce, work shifts, workplace testing, sequence of confirmed COVID-19 cases identified, and the company COVID-19 risk assessment.A confirmed case was defined as an individual who worked in the plant and had a positive polymerase chain reaction (PCR) test or rapid antigen test by lateral flow device (LFT) for SARS-CoV-2 during the outbreak period. Anonymised information about positive cases, including dates of the positive tests, obtained from PHE and the company was combined. The PHE case list contained information on the number of employees who tested positive from 29 May 2021 up to 15 June 2021, including symptom onset dates, follow-up test dates, work shifts, whether working from home, linked positive tests in family members and S-gene positive status of the PCR test samples. A detectable S-gene was a proxy for identifying Delta variant of SARS-CoV-2 infection after April 2021 in England. The company’s case list contained information on the number of employees who tested positive from 3 January 2021 to 27 June 2021, including information on test dates, work shifts, job title and work areas. When the two case lists were compared, there were 11 cases  in the PHE case list that did not appear in the company case list. These cases were added to the company case list to provide the final combined case list. The outbreak dynamics were illustrated using an epidemic curve, produced using Stata statistical software 17 , using wThe on-site environmental assessment and surface sampling were carried out on 24 and 25 June 2021 when the outbreak was declining but there were still occasional positive cases identified in the workforce. The environmental assessment was conducted following previously developed data collection frameworks and tools , which i2) (as a proxy for ventilation), relative humidity and temperature were taken on the two-day site visit, as well as longitudinally over two weeks, from 25 June to 11 July 2021. The real-time monitors  were left in various locations around the plant where workers may congregate. They were positioned at around head height at locations that would avoid direct worker interaction and away from ventilation grilles. Data were logged every minute and a moving 30-min average applied. Honeywell BW Solo CO2 monitors have a resolution of 100 ppm, an estimated limit of detection of around 300 ppm, and an upper limit of 50,000 ppm. CO2 concentration levels can be used as a surrogate to indicate the adequacy of ventilation provision in occupied indoor spaces providing there are no other CO2 sources in the space. In multi-occupant spaces that are used regularly, a CO2 concentration routinely greater than 1500 ppm or a ventilation rate below 5 l/s/person is considered indicative of inadequate ventilation [2, relative humidity and temperature were analysed using Microsoft Excel version 2302.Spot measurements for carbon dioxide . Collected samples were sent to laboratories at PHE Porton for analysis. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) for both ORF1ab and nucleocapsid (N) gene targets was performed in duplicate using the VIASURE SARS-CoV-2 Real Time PCR Detection Kit  in accordance with the manufacturer’s instructions. The reportable detection limit was a crossing threshold (Ct) value of 38.0 as recommended by the manufacturer’s instructions. Positive samples reported in analysis included confirmed positive samples and suspected positive samples. Confirmed positive samples were those with both replicates testing positive for at least one target, and suspected positive samples were those with a single replicate testing positive for at least one target. Positive samples with cycle threshold (Ct) values of 35.0 or lower were sent for further whole genome sequencing (WGS).For surface sampling for SARS-CoV-2 RNA, samples were collected from high touch points and other areas of interest (areas where workers congregated and workplaces throughout the site) using previously described methods ,31. The The first confirmed case linked to this outbreak was identified on 29 May 2021. Case numbers then increased, leading to an outbreak being declared on 8 June 2021 by PHE. This time-period corresponded with the emergence of the Delta variant (B.1.617.2) of SARS-CoV-2 in the UK and this outbreak occurred as the local community infection rate started to increase . The rolThe meat-processing plant employed 1541 workers who worked in dayshifts, nightshifts, or a combination of these across multiple work areas, such as processing, hygiene, quality assurance, engineering, despatch and transportation. Some worked part-time. Most of the workers were permanent employees with a small number  of agency staff and contractors. About a quarter (24.2%) of the workers were aged 50 or over. There were more men (56.8%) than women (43.1%). There were two work shifts, a dayshift  and a nightshift . Saturday and Sunday daytime were non-operational periods. Between the dayshift and the nightshift, there was a production hygiene shift (15:30–22:00) to clean the whole production area.Approximately 380 staff members were working on production, either in a day or a nightshift. However, the nightshift had generally a more consistent and constant workforce. A company coach service was available, transporting on average 150 workers per dayshift and 104 workers per nightshift.During the outbreak period, a total of 63 confirmed cases were identified, with an estimated overall attack rate of 4.1% (63/1541). A timeline of confirmed cases is shown in The first confirmed case was identified in a night-shift worker on 29 May, with a further seven cases reported in the following eight days. The first case reported in a day-shift worker was on 7 June. This case was a partner of a night-shift case who tested positive three days earlier  and when travelling on the company coaches. Face coverings here included reusable fabric face masks provided by the company to workers. Workers were also allowed to use their own face coverings of any type. All types of face coverings were taken home to wash, and were not included in the general workwear laundry facility on-site, which provided washing for general production area coats and trousers. Supervision was provided for enforcing face coverings in these areas, and the observed adherence was good.In the production areas, physical distancing could not always be maintained. There were crowded areas where production lines were close together, and people walked past in close proximity (<2 m). It was not always possible to place workers back-to-back or side-by-side rather than face-to-face when they worked closer than 2 m. Screens were erected between those working closely together but this was not always possible because of the production process or the production line configuration. In these situations, workers were required to wear both a face covering and a face visor, but it was observed that face coverings were not always worn in such situations.The production areas were mandatory hearing protection zones. Noise levels in the meat material intake, packing and the main production areas were recorded at 80–83 dB(A) . A combiAs part of the meat-processing activities, personal protective equipment in production areas included gloves, aprons, gauntlets and beard snoods where needed. For COVID-19 controls, personal visors were mandatory in the production areas and face coverings were required only if physical distancing was not reasonably practical. However, engineers would wear a face covering in production areas as visors were impractical for their work roles.The factory was sanitised and deep cleaned at regular intervals during each 24-h period. Frequent hand washing was part of standard food hygiene requirements and had been reinforced through various communication platforms. Numerous hand sanitiser stations had been installed across the site. Signs to support the hand hygiene process were displayed above the sinks.A number of non-production areas were fogged daily, Sunday to Thursday. Fogging was undertaken using Safe Zone Plus A006 EV viricidal disinfectant, containing 2-aminoethanol (0.1–1%), didecyldimethylammonium chloride (DDAC) (0.1–1%) and potassium carbonate (0.1–1%). The manufacturer’s information for this product stated that it was “effective against all enveloped viruses, including Coronavirus”, but it did not specifically state SARS-CoV-2. A spreadsheet containing details of fogging frequency and times showed that fogging was undertaken extensively, including once daily in the main office block; twice daily in the reception area, engineering workshop and logistics office; and three times daily in the canteen, locker rooms and toilets.Soon after the declaration of the outbreak, on-site surge PCR testing was implemented for one week, between 13 and 20 June, testing 500 out of 860 staff on-site. The voluntary LFTs were stopped during this period and were reinstated on 20 June. Vaccination clinics were set up on-site and approximately 100 workers received vaccinations, including second doses. Additional coaches (increased from four to eight) were deployed to allow physical distancing in shared work transportation.In the non-production areas, there were two mechanical ventilation systems and some natural ventilation. The air handling units in these areas  in the production areas  and nine vertical baggers (Ilapack VFFS). It was reported that the packing machine CO2 works on demand during production and is not switched off at the main inlet at the end of the shift. The CO2 data from the main production area and areas connected to it cannot therefore be used to assess the adequacy of ventilation in these areas. None of the areas away from the main production area had levels greater than 1500 ppm.Spot measurements of COon areas  but it w2 measurements were also carried out over two weeks to assess ventilation  in the washing area above sinks at the office-production entrance  and the main locker room  were within normal ranges. 2 level in the main locker room. The mid-week CO2 levels remained below 1500 ppm. There was generally a peak of short duration at the beginning and end of each shift. There were also broader peaks within the shift period.COReal-time measurements of temperature and humidity were also carried out over two weeks in both production and non-production areas . In geneA total of 60 surface samples were collected across the site on 24 and 25 June to assess the level of viral contamination. Only one sample was confirmed positive for SARS-CoV-2 RNA  and six samples  identified as suspected positive . The engThis investigation of a COVID-19 outbreak at a large meat-processing plant identified many potential transmission risk factors, including high occupancy level, low temperature, high humidity, high noise levels, night-shift work and shared work transportation which may have contributed to cases detected in this workplace . Most ofBefore the start of the outbreak at this site, England moved to further easing of COVID restrictions, as infection rates continued to decrease in the community, but COVID-secure rules for workplace and businesses remained . The outIn general, there are three major routes where SARS-CoV-2 transfer from an infected person to a susceptible individual through respiratory droplets and aerosols: 1) the inhalation (airborne) route, which can occur at any distance but is more likely when people are in close proximity; (2) the spray (droplet) route, which usually occurs in close proximity; and (3) the touch (fomite) route [ the inhaProduction lines are designed for maximum efficiency and productivity, with workers working closely together where physical distance is difficult to maintain at all times. Vocal effort for conversation at a distance of 1 m has to increase when ambient noise levels are above 65 dB(A) . Previou2 were found in the production areas, with many exceeding 1500 ppm. However, we could not determine if the high CO2 readings were from the presence of CO2 from the packaging process or from the lack of ventilation. The amount of CO2 being released from the packing process to the workplace air was not assessed by the study. The high level of CO2 in the production areas may also imply a decreased pH level, which could possibly increase SARS-CoV-2 stability in the air and therefore the transmissibility of the virus [The ventilation systems for the production areas and non-production areas were maintained by two different external contractors. The company COVID-19 risk assessment did not provide information on the ventilation assessment in the production areas. High levels of COhe virus . Such fihe virus .SARS-CoV-2 is sensitive to heat but is relatively stable at 4 °C . AnalysiFace masks refer to surgical or respiratory masks. Face coverings include broader types and materials such as reusable cloth masks or simple scarves that cover the nose and mouth. In the outbreak site, face coverings (mostly reusable fabric masks) were mandatory in communal areas and on coaches, but visors were mandatory in the production areas. Wearing additional face coverings in the production areas became mandatory if physical distancing was not possible, and workers had to work face-to-face. There is substantial evidence that face masks and coverings will help to reduce emission of virus (source control) from infectious individuals and to protect others from exposure to droplets and large aerosols containing the virus . A previThe company provided staff with reusable fabric face coverings which were taken home to clean, as well as all types of face covering used, rather than washed in the general workwear laundry facility. A randomised control trial in hospital healthcare workers, focusing on seasonal respiratory viruses, found that those who self-washed their cloth masks by hand had double the risk of infection of those who used the hospital laundry and that double-layered cloth masks washed in the hospital laundry were as protective against respiratory infection as medical masks . This suVisor-wearing alone would not protect workers from the potential risk of transmission in the production areas . On the The proportion of positive surface samples (11.7% 7/60 samples) found in this outbreak site is similar to the positive rate of 8% found on high-touch surfaces in a community setting in the U.S., April to June 2020 . HoweverSimilar to other studies of COVID-19 workplace outbreaks , the outThe first confirmed case in the day-shift staff was likely due to household transmission as the partner of this case, who also worked in the same factory but on nightshifts, tested positive four days prior. However, the outbreak in the day-shift staff did not develop much further.Although there were some challenges identified, the observed COVID-19 control measures in the non-production areas were implemented relatively well. The company had an internal test and trace system led by senior staff, and the company also offered full pay for COVID-19-related self-isolation. The food safety controls already in place to reduce bacteria were also likely to be successful in reducing virus particles on surfaces and on hands.In summary, all routes of transmission may have played a part in this outbreak. Although there were challenges in their implementation, physical distancing, face coverings (including visors) and using physical barriers could have reduced the spray (droplet) transmission. Hand hygiene, extensive surface cleaning, wearing gloves and face coverings or visors (source control) could have reduced fomite transmission. However, the efficacy of the ventilation and the suitability of the face coverings/visor used could not be assessed adequately to support mitigating the potential inhalation transmission in the production areas. An epidemiological study involving a large number of meat-processing facilities in Nebraska, U.S., concluded that control measures such as mandatory face coverings and physical barriers would block mainly the larger respiratory droplets, and they would not fully protect workers against inhalation transmission, and the interventions should be accompanied by ventilation enhancements and worker education on face covering use and adherence .There were challenges in the implementation of control measures in the meat-processing plant, including financial, production and reputational impacts on the employer, as well as workers’ worries about incomes or the incomes of the people they live with if they had to isolate. However, working with the local public health team, the company’s rapid testing, coupled with local contact tracing were likely to have been crucial in controlling the outbreak. Following the new measures, the cases in the workplace declined while the cases in the local community continued to increase rapidly. These are consistent with findings from previously studies ,51,52.Although our data could not reliably assess the adequacy of ventilation in the production areas of this workplace, it is well-demonstrated that effective ventilation can reduce risk of inhalation transmission . If a reAt this outbreak site, there was an extensive fogging programme. Currently no evidence supports the effectiveness of fogging in controlling SARS-CoV-2 transmission, but the financial costs and the environmental impact could be substantial. In comparison, the economic cost of face coverings could be relatively low and seems to be a cost-effective measure, as part of multi-layered controls, to contribute to reducing all routes of the virus transmission . NeverthMany different factors can contribute to a workplace outbreak. Therefore, a multi-layered approach is required to prevent and control outbreaks . The choOur study has several limitations. The investigation was carried out as the outbreak was subsiding and was unable to conclusively establish transmission within the workplace. Therefore, the interpretation of the influence of different environmental factors, work activities and mitigation measures on the virus transmission is limited. The information on case numbers was based on non-exhaustive screening which limits the ability to establish complete chains of transmission between workers.2 measurements to assess the adequacy of ventilation provision in the occupied indoor workspaces. However, it was recognised that CO2 was also used in some of the meat packaging processes which affects the interpretation of the CO2 measurement results in the production areas. Therefore, no firm conclusion could be made on the adequacy of the ventilation in these areas. An alternative ventilation assessment approach should be considered in this situation, such as calculating an indicative air change rate from mechanical ventilation flow rates and room dimensions (where available or accessible). Given the right circumstances, the decay rate of CO2 (or a suitable tracer gas) can be used to estimate the ventilation rate [This study used COion rate . Some knFurthermore, information on the potential transmission risk factors and control measures were based on self-reports by company management, company records and study team members’ on-site observations. Therefore, this study cannot establish causal relationships between the risk factors investigated and the outbreak. Neither can this study assess conclusively the effectiveness of the control measures implemented. Nevertheless, it has identified potential transmission risk factors that were likely to have contributed to the outbreak.Meat-processing plants appear to be at increased risk of outbreaks of COVID-19 occurring even with a wide range of control measures in place because of many work- and non-work-related risk factors, challenges in fully implementing the control measures and the challenges in the nature of the work. A high density of workers and an unfavourable mix of environmental conditions might play significant roles in the increased risk of virus transmission in the production areas. Further investigation of the production area ventilation effectiveness would be needed. Shared work transport is often required in these types of workplaces and could contribute to transmission within the workforce, even though this activity is difficult for employers to control.This COVID-19 outbreak at the large meat-processing plant was likely contained by proactive leadership re-evaluating key controls and engaging with local health protection specialists. Leadership that encourages and monitors workers’ compliance with various control measures, including early identification of infectious cases through comprehensive workplace testing and contact tracing strategies, physical distancing, hand hygiene, surface cleaning, providing suitable sick pay policy and encouraging vaccination, are all important in the rapid response to control SARS-CoV-2 transmission or other similar respiratory infectious disease outbreaks in the workplace.Our study illustrates the importance of site-specific risk assessments to inform choices made on the range of control measures, considering all potential routes of the virus transmission. The findings add to the existing literature on risk factors and control measures for COVID-19 outbreaks in meat-processing plants globally and contribute to future pandemic preparedness.Meat-processing plants are part of the national essential infrastructure and could develop and rehearse, in collaboration with local health protection teams, an outbreak response plan for controlling future outbreaks of infectious diseases and to maintain business continuity.


New treatments that utilize targeted therapeutic agents or invigorations of the host immune system to destroy cancer cells are not effective against all cancers or responding patients. The mechanism underlying this failure is the ability of cancer cells to escape destruction and remain resistant to therapy. Understanding the gene products that make cancer cells resistant is beneficial in developing new drugs that inhibit resistant factors. One factor controlling the resistance in cancer cells is the gene regulator or transcription factor (TF) Yin Yang 1 (YY1). High levels of YY1 were detected in resistant cancer cells, while the inhibition restored sensitivities to cytotoxic therapies. This review discusses how YY1 overexpression regulates death protective proteins that control cancer cell resistance. Targeting YY1 in cancer cells for its inhibition or targeting its protective proteins will reverse resistance and allow for cancer cells to respond to therapies, tumor regression and the prolongation of survival.Cancer is a leading cause of death among the various diseases encountered in humans. Cancer is not a single entity and consists of numerous different types and subtypes that require various treatment regimens. In the last decade, several milestones in cancer treatments were accomplished, such as specific targeting agents or revitalizing the dormant anti-tumor immune response. These milestones have resulted in significant positive clinical responses as well as tumor regression and the prolongation of survival in subsets of cancer patients. Hence, in non-responding patients and non-responding relapsed patients, cancers develop intrinsic mechanisms of resistance to cell death via the overexpression of anti-apoptotic gene products. In parallel, the majority of resistant cancers have been reported to overexpress a transcription factor, Yin Yang 1 (YY1), which regulates the chemo-immuno-resistance of cancer cells to therapeutic anticancer cytotoxic agents. The relationship between the overexpression of YY1 and several anti-apoptotic gene products, such as B-cell lymphoma 2 protein (Bcl-2), B-cell lymphoma extra-large (Bcl-xL), myeloid cell leukemia 1 (Mcl-1) and survivin, is investigated in this paper. The findings demonstrate that these anti-apoptotic gene products are regulated, in part, by YY1 at the transcriptional, epigenetic, post-transcriptional and translational levels. While targeting each of the anti-apoptotic gene products individually has been examined and clinically tested for some, this targeting strategy is not effective due to compensation by other overexpressed anti-apoptotic gene products. In contrast, targeting YY1 directly, through small interfering RNAs (siRNAs), gene editing or small molecule inhibitors, can be therapeutically more effective and generalized in YY1-overexpressed resistant cancers. Yin Yang 1 (YY1) is a transcription factor of the GLI-Kruppel gene family ubiquitously expressed in humans and is known to regulate the activation and repression of transcription . Its actThe transcription factor YY1 consists of 414 amino acids with a molecular weight of ~65,000 Daltons and is encoded on chromosome 14 in humans . HomodimGRP) genes , is currently in preparation to bridge the gap and need for a specific inhibitor of YY1. Ideally, the inhibition of YY1 will lead to the sensitization of resistant tumor cells to drug-induced apoptosis and encourage tumor growth inhibition. The specific YY1 inhibitor (Inh-YY1) inhibited YY1-DNA and can be traced to the activator activity on the s of YY1 . Bonavids of YY1 . The ides of YY1  (Figure Due to the fact that anti-apoptotic proteins are highly associated with poor prognosis and cancer resistance, the direct therapeutic targeting of these members has become an important new strategy. Targeting Bcl-2 family members has been thoroughly reviewed ,124,125,The targeting of these anti-apoptotic proteins is a novel strategy for reversing resistance in cancers with the overexpression of these proteins. Due to the fact that resistance to apoptosis is highly connected to resistance of many conventional therapies, targeting the proteins that promote survival is very likely to be effective. Additionally, the use of these targeting strategies in addition to other novel treatments may prove to be synergistic. It would be ideal to target treatment resistance at several levels and novel drug combinations should be studied.Our findings highlight that the transcription factor YY1 has the potential to promote or repress oncogenic proliferation in cancer cells depending on several factors. The regulation of YY1 expression can be traced to the transcription level through autoregulation, the NF-κB/YY1/microRNA-10a circuit and the NF-κB/Snail/YY1/RKIP regulatory loop ,109. PosIn cancer cells, YY1 has the ability to promote and repress tumor growth . SeveralYY1 also has implications with T-cell exhaustion, attributing its role in resistance to cytotoxic T cells . YY1 regThe present paper reviewed novel perspectives on the relationship between the overexpression of YY1 in cancer and the expression of anti-apoptotic proteins, offering valuable insights into the role of YY1 in regulating resistance to apoptosis-induced cytotoxic therapies. Various mechanisms were discussed by which YY1 regulates the expression of the anti-apoptotic proteins, Bcl-2, Bcl-xl, Mcl-1 and survivin, both directly at the transcriptional and post-transcriptional levels and indirectly. We also delved into the functional consequences of the YY1-mediated regulation of these anti-apoptotic proteins and highlighted the role of YY1 in conferring resistance to apoptosis and, hence, promoting tumor cell survival and metastasis and significantly contributing to cancer resistance in various cancer types to both chemotherapy and immunotherapy.This report also discussed the potential clinical significance of YY1 and anti-apoptotic proteins as potential targets in cancer treatment. It also explored various therapeutic strategies that have been reported to modulate YY1 expression or activity, including RNA-based approaches, small molecules, peptides and a small-molecule-specific YY1 inhibitor. These various YY1 inhibitors are discussed as significant chemo-immuno-sensitizers when used in combination to treat resistant cancer cells. It was also discussed the preference of targeting YY1 as its inhibition will be manifested by various consequential effects, not only in the inhibition of anti-apoptotic proteins, but also in the inhibition of cell proliferation, invasion and cancer stem cells.In this report, we only focused on very few anti-apoptotic proteins and further research must address other anti-apoptotic proteins as well as the regulation of pro-apoptotic proteins. We addressed the challenges we are facing with the clinical application of targeting YY1 and more research is needed to validate its potential clinical application. Clearly, it is also important to identify biomarkers and the patient subgroups who will benefit from targeting YY1 or anti-apoptotic proteins.In conclusion, this report provided a comprehensive analysis of the current understanding of the interplay between YY1 and anti-apoptotic proteins in cancer. It highlighted the significance of YY1 in promoting cancer cell survival and therapy resistance via the YY1 regulation of anti-apoptotic proteins. It underscored the potential of YY1 and anti-apoptotic proteins as therapeutic targets in cancer treatment and urgently suggested further research to translate the findings into clinical applications in cancer patients.